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Collaborative Research: Travel: NSF Student Travel Grant for ACM/IEEE Great Lakes Symposium on VLSI (GLSVLSI) 2024
|
NSF
|
08/01/2024
|
01/31/2025
| 8,001 | 8,001 |
{'Value': 'Standard Grant'}
|
{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}
|
{'SignBlockName': 'Hu, X. Sharon', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928910'}
|
The objective of this initiative is to enhance student participation at the Great Lakes Symposium on Very Large Scale Integration (VLSI) (GLSVLSI 2024) in Clearwater, Florida, USA, by providing financial support. This support aims to encourage attendance among students across diverse VLSI areas, such as circuits and systems, computer-aided design, emerging computing, hardware security, machine learning, and microelectronic education. Given the diverse expertise of GLSVLSI attendees, spanning various VLSI domains, sponsoring student participation is expected to foster interdisciplinary collaboration and cultivate a dynamic academic community. Through active involvement in GLSVLSI sessions, poster presentations, and networking opportunities, students can contribute to knowledge advancement in their fields while gaining valuable insights from fellow scholars and experts. <br/><br/>This travel grant for GLSVLSI 2024 seeks to provide financial assistance to 20 US-based student attendees, covering their registration fees. A portion of the grant, totaling 25%, will be allocated to support diversity, including undergraduates, females, and people from underrepresented populations. This initiative aims to enhance institutional, geographic, and demographic diversity and inclusion within the academic community, ensuring equitable access to scholarly opportunities for students from varied backgrounds. By removing financial barriers and facilitating student participation, the grant facilitates knowledge exchange, collaboration, and the dissemination of research findings, thereby enriching the academic experience of the symposium and advancing both the field and principles of diversity, equity, and inclusion.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/31/2024
|
07/31/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430655
|
{'FirstName': 'Inna', 'LastName': 'Partin-Vaisband', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Inna Partin-Vaisband', 'EmailAddress': '[email protected]', 'NSF_ID': '000730148', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Illinois at Chicago', 'CityName': 'CHICAGO', 'ZipCode': '606124305', 'PhoneNumber': '3129962862', 'StreetAddress': '809 S MARSHFIELD AVE M/C 551', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'IL07', 'ORG_UEI_NUM': 'W8XEAJDKMXH3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ILLINOIS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Illinois Chicago', 'CityName': 'CHICAGO', 'StateCode': 'IL', 'ZipCode': '606124305', 'StreetAddress': '809 S MARSHFIELD AVE M/C 551', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'IL07'}
|
{'Code': '779800', 'Text': 'Software & Hardware Foundation'}
|
2024~8001
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430655.xml'}
|
Collaborative Research: Travel: NSF Student Travel Grant for ACM/IEEE Great Lakes Symposium on VLSI (GLSVLSI) 2024
|
NSF
|
08/01/2024
|
01/31/2025
| 2,001 | 2,001 |
{'Value': 'Standard Grant'}
|
{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}
|
{'SignBlockName': 'Hu, X. Sharon', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928910'}
|
The objective of this initiative is to enhance student participation at the Great Lakes Symposium on Very Large Scale Integration (VLSI) (GLSVLSI 2024) in Clearwater, Florida, USA, by providing financial support. This support aims to encourage attendance among students across diverse VLSI areas, such as circuits and systems, computer-aided design, emerging computing, hardware security, machine learning, and microelectronic education. Given the diverse expertise of GLSVLSI attendees, spanning various VLSI domains, sponsoring student participation is expected to foster interdisciplinary collaboration and cultivate a dynamic academic community. Through active involvement in GLSVLSI sessions, poster presentations, and networking opportunities, students can contribute to knowledge advancement in their fields while gaining valuable insights from fellow scholars and experts. <br/><br/>This travel grant for GLSVLSI 2024 seeks to provide financial assistance to 20 US-based student attendees, covering their registration fees. A portion of the grant, totaling 25%, will be allocated to support diversity, including undergraduates, females, and people from underrepresented populations. This initiative aims to enhance institutional, geographic, and demographic diversity and inclusion within the academic community, ensuring equitable access to scholarly opportunities for students from varied backgrounds. By removing financial barriers and facilitating student participation, the grant facilitates knowledge exchange, collaboration, and the dissemination of research findings, thereby enriching the academic experience of the symposium and advancing both the field and principles of diversity, equity, and inclusion.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/31/2024
|
07/31/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430656
|
{'FirstName': 'Srinivas', 'LastName': 'Katkoori', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Srinivas Katkoori', 'EmailAddress': '[email protected]', 'NSF_ID': '000283049', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of South Florida', 'CityName': 'TAMPA', 'ZipCode': '336205800', 'PhoneNumber': '8139742897', 'StreetAddress': '4202 E FOWLER AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '15', 'CONGRESS_DISTRICT_ORG': 'FL15', 'ORG_UEI_NUM': 'NKAZLXLL7Z91', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF SOUTH FLORIDA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of South Florida', 'CityName': 'TAMPA', 'StateCode': 'FL', 'ZipCode': '336205800', 'StreetAddress': '4202 E FOWLER AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '15', 'CONGRESS_DISTRICT_PERF': 'FL15'}
|
{'Code': '779800', 'Text': 'Software & Hardware Foundation'}
|
2024~2001
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430656.xml'}
|
Collaborative Research: NLI: Design and Development: Priming to support sustainable design and sustainable mindsets
|
NSF
|
09/15/2024
|
08/31/2027
| 200,867 | 200,867 |
{'Value': 'Standard Grant'}
|
{'Code': '07050000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'EEC', 'LongName': 'Div Of Engineering Education and Centers'}}
|
{'SignBlockName': 'Matthew A. Verleger', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922961'}
|
As the challenges facing society grow more complex, there is increasing recognition that engineers must consider the social and environmental contexts in which their designs will exist in order to create effective products, systems, and processes that improve global quality of life. However, engineering curricula often focuses on technical design performance, and provides little training on how to contend with environmental and social challenges, leaving students ill-equipped to address sustainability during design. In support of the goals of the Research in the Formation of Engineers program and the NSF-Lemelson Initiative on Environmental and Social Sustainability in Engineering Education, this project will advance understanding of how to support engineering students’ preparation to address global social and environmental sustainability challenges. Specifically, this project will advance an educational approach focusing on priming that is adaptable across engineering disciplines and provide guidance for implementing this approach to emphasize social and environmental sustainability within existing curricula. Emphasizing sustainability in engineering may particularly resonate with and attract individuals from diverse and minoritized backgrounds drawn to impact-driven careers. Therefore, this project can contribute to creating a more inclusive and representative engineering workforce ready to address socio-technical challenges. <br/><br/>This project seeks to develop, implement, and assess priming as an educational strategy to promote sustainable engineering design decision-making at the University of Michigan and the University of Arizona. Priming involves explicitly introducing a stimulus to students and assessing the subsequent response. Multiple prior studies have shown that, in controlled behavioral experiments, explicit sustainability language in problem statements results in better consideration of sustainability in subsequent design decisions. Additionally, supporting students to handle socio-technical complexity has been hypothesized to promote students’ sense of engineering agency beliefs and self efficacy. In this project, the team will adopt a mixed methods approach to investigate (1) the potential to scale up priming for sustainability as an engineering education intervention, (2) the role of priming on sustainable engineering design, (3) the impact of priming for sustainability on engineering students’ sense of agency and self-efficacy. The project team will first develop a range of sustainability primes, informed by literature on engineering education, design processes, sustainability competencies, and the Lemelson Initiative’s Engineering for One Planet Framework. The team will work with engineering instructors to tailor sustainability primes to fit within existing engineering design courses. The team will then collect and analyze qualitative and quantitative data from engineering instructors and students. Initial interviews will be conducted with engineering instructors to understand their course and learning objectives and to identify opportunities to add in priming for sustainability. After the sustainability primes are implemented in courses, interviews will be conducted with students to garner detailed insights into their experiences in engineering design courses, the design artifacts resulting from their courses, and their perspectives on sustainability in engineering. Validated tools will be used to measure changes in students’ engineering agency beliefs and self-efficacy before and after exposure to sustainability primes within engineering design courses. The expected contributions of this project are multifaceted. First, this project will provide guidance for integrating sustainability into engineering design curricula, resulting in more sustainable design decisions by students. By creating adaptable priming interventions, the project will provide a scalable tool for use by a broad set of engineering institutions and disciplines to emphasize sustainability. Additionally, this project will enhance an understanding of the relationship between students' beliefs about their engineering capabilities and their consideration of sustainability, an area that remains underexplored yet has potential to broaden participation and retention in engineering education.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/02/2024
|
08/02/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430676
|
{'FirstName': 'Hannah', 'LastName': 'Budinoff', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hannah Budinoff', 'EmailAddress': '[email protected]', 'NSF_ID': '000837370', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Arizona', 'CityName': 'TUCSON', 'ZipCode': '85721', 'PhoneNumber': '5206266000', 'StreetAddress': '845 N PARK AVE RM 538', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Arizona', 'StateCode': 'AZ', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'AZ07', 'ORG_UEI_NUM': 'ED44Y3W6P7B9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ARIZONA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Arizona', 'CityName': 'TUCSON', 'StateCode': 'AZ', 'ZipCode': '85721', 'StreetAddress': '1127 E. James E. Rogers Way Room 129', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Arizona', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'AZ07'}
|
{'Code': '134000', 'Text': 'EngEd-Engineering Education'}
|
2024~200867
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430676.xml'}
|
Collaborative Research: NLI: Design and Development: Priming to support sustainable design and sustainable mindsets
|
NSF
|
09/15/2024
|
08/31/2027
| 197,710 | 197,710 |
{'Value': 'Standard Grant'}
|
{'Code': '07050000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'EEC', 'LongName': 'Div Of Engineering Education and Centers'}}
|
{'SignBlockName': 'Matthew A. Verleger', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922961'}
|
As the challenges facing society grow more complex, there is increasing recognition that engineers must consider the social and environmental contexts in which their designs will exist in order to create effective products, systems, and processes that improve global quality of life. However, engineering curricula often focuses on technical design performance, and provides little training on how to contend with environmental and social challenges, leaving students ill-equipped to address sustainability during design. In support of the goals of the Research in the Formation of Engineers program and the NSF-Lemelson Initiative on Environmental and Social Sustainability in Engineering Education, this project will advance understanding of how to support engineering students’ preparation to address global social and environmental sustainability challenges. Specifically, this project will advance an educational approach focusing on priming that is adaptable across engineering disciplines and provide guidance for implementing this approach to emphasize social and environmental sustainability within existing curricula. Emphasizing sustainability in engineering may particularly resonate with and attract individuals from diverse and minoritized backgrounds drawn to impact-driven careers. Therefore, this project can contribute to creating a more inclusive and representative engineering workforce ready to address socio-technical challenges. <br/><br/>This project seeks to develop, implement, and assess priming as an educational strategy to promote sustainable engineering design decision-making at the University of Michigan and the University of Arizona. Priming involves explicitly introducing a stimulus to students and assessing the subsequent response. Multiple prior studies have shown that, in controlled behavioral experiments, explicit sustainability language in problem statements results in better consideration of sustainability in subsequent design decisions. Additionally, supporting students to handle socio-technical complexity has been hypothesized to promote students’ sense of engineering agency beliefs and self efficacy. In this project, the team will adopt a mixed methods approach to investigate (1) the potential to scale up priming for sustainability as an engineering education intervention, (2) the role of priming on sustainable engineering design, (3) the impact of priming for sustainability on engineering students’ sense of agency and self-efficacy. The project team will first develop a range of sustainability primes, informed by literature on engineering education, design processes, sustainability competencies, and the Lemelson Initiative’s Engineering for One Planet Framework. The team will work with engineering instructors to tailor sustainability primes to fit within existing engineering design courses. The team will then collect and analyze qualitative and quantitative data from engineering instructors and students. Initial interviews will be conducted with engineering instructors to understand their course and learning objectives and to identify opportunities to add in priming for sustainability. After the sustainability primes are implemented in courses, interviews will be conducted with students to garner detailed insights into their experiences in engineering design courses, the design artifacts resulting from their courses, and their perspectives on sustainability in engineering. Validated tools will be used to measure changes in students’ engineering agency beliefs and self-efficacy before and after exposure to sustainability primes within engineering design courses. The expected contributions of this project are multifaceted. First, this project will provide guidance for integrating sustainability into engineering design curricula, resulting in more sustainable design decisions by students. By creating adaptable priming interventions, the project will provide a scalable tool for use by a broad set of engineering institutions and disciplines to emphasize sustainability. Additionally, this project will enhance an understanding of the relationship between students' beliefs about their engineering capabilities and their consideration of sustainability, an area that remains underexplored yet has potential to broaden participation and retention in engineering education.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/02/2024
|
08/02/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430677
|
{'FirstName': 'Julia', 'LastName': 'Kramer', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Julia Kramer', 'EmailAddress': '[email protected]', 'NSF_ID': '000930665', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'ZipCode': '481091079', 'PhoneNumber': '7347636438', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'MI06', 'ORG_UEI_NUM': 'GNJ7BBP73WE9', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MICHIGAN', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'StateCode': 'MI', 'ZipCode': '481091079', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'MI06'}
|
{'Code': '134000', 'Text': 'EngEd-Engineering Education'}
|
2024~197710
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430677.xml'}
|
ENG-SEMICON: EPMD: Engineering Perovskite LEDs
|
NSF
|
09/01/2024
|
08/31/2027
| 425,000 | 425,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Dominique Dagenais', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922980'}
|
The prevalence of artificial intelligence (AI) and of internet of things (IoT) in our life has resulted in an exponential growth in the amount of data being transmitted at any second in a day at an unprecedented rate. The total bit rate for internet traffic already surpassed that of telephone traffic at the beginning of the 21st century and continued to grow at a rate of ~100 times per decade. While the total internet traffic is high, a decade ago it was already small compared to the data sent over shorter links in data centers which has been growing at an even higher rate. More recently, massively parallel computations that are critical for machine learning (ML) and data analysis have driven bandwidth requirement for ML supercomputers, which have become a major contributor for information data. The growth rate of global electricity usage by information processing and computing has surpassed that of electricity generation capacity for over a decade, with analysis showing it consumes the majority of global electricity on the horizon. This energy consumption has caused serious alarm to our environment. Without major reduction in energy per bit of information data, the bandwidth of information processing and computing cannot continue to grow. This demands innovations in technology hardware and infrastructure for computing and communication.<br/>Using light to carry information data has not only enabled long-haul high-capacity communication networks and revolutionized our communication technologies, but also offers a route to higher interconnect densities and reduced energy consumption in data centers and ML supercomputers. A key component in optical interconnects is the transmitter, which traditionally utilizes semiconductor lasers. They have high optical performance but face the challenge of high energy consumption and cost, in addition to difficult integration with their Si CMOS drive circuits which further leads to high system-level energy consumption. LEDs offer a promising alternative as low-cost photonic sources in optical interconnects. However, conventional LEDs cannot be easily integrated with Si CMOS either. Metal-halide perovskite semiconductors are solution-processable materials with high optoelectronic properties and facile integration compatibility with many platforms including Si CMOS. The objective of the proposed research is to achieve perovskite LEDs with high modulation bandwidth. Three research approaches, each carrying its own intellectual merit, will be conducted in synergy to achieve the goal. They are: (1) Engineering perovskite semiconductor materials and device design to minimize resistance and increase LED speed. (2) Optimizing modulation format for high-bandwidth operation using data-driven learning. (3) Developing a process for monolithic integration of perovskite micro-LEDs on Si to minimize overall parasitics, improve system-level modulation bandwidth and reduce energy consumption.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/25/2024
|
07/25/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430679
|
{'FirstName': 'Lih', 'LastName': 'Lin', 'PI_MID_INIT': 'Y', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lih Y Lin', 'EmailAddress': '[email protected]', 'NSF_ID': '000489940', 'StartDate': '07/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'ZipCode': '981951016', 'PhoneNumber': '2065434043', 'StreetAddress': '4333 BROOKLYN AVE NE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Washington', 'StateCode': 'WA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'WA07', 'ORG_UEI_NUM': 'HD1WMN6945W6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WASHINGTON', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'StateCode': 'WA', 'ZipCode': '981951016', 'StreetAddress': '4333 BROOKLYN AVE NE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Washington', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'WA07'}
|
{'Code': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}
|
2024~425000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430679.xml'}
|
CAREER: Macroevolutionary Biomechanics: Integrating Morphology, Mechanical Models, and Phylogenetic Comparative Methods to Understand the Evolution of Swimming Performance in Frogs
|
NSF
|
02/01/2024
|
07/31/2025
| 900,263 | 500,263 |
{'Value': 'Continuing Grant'}
|
{'Code': '08090300', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Miriam Ashley-Ross', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924997'}
|
Biomechanics has contributed a rich understanding of the physical principles that dictate organismal form and function, but the field has been slow to incorporate study of the evolution of mechanical diversity. In this CAREER project, the principal investigator (PI) will combine experiments on live organisms, computer modeling, and statistical analyses of the evolution of species differences to understand the evolution of diversity of body form and movement. The project will focus on (1) how different body structures scale with body size; (2) how the size of these structures and different behavioral strategies affect aquatic locomotion (i.e. swimming); (3) how sensitive swimming performance is to variation in such variables; and (4) how these relationships between form and function have affected long-term evolutionary change in swimming performance across >140 species of frogs and toads around the world. The key intellectual contribution of the project will be to develop an evolutionarily explicit approach to studies of form, function, and their diversity across species. The project will also more broadly support scientific capacity in the USA by (1) training secondary science teachers in research methods, evolutionary concepts, and integration of research into their classrooms; (2) training undergraduate students in the study of animal movement and research methods through in-class research projects; and (3) training young researchers in biomechanics to more directly incorporate evolutionary analysis methods into their projects. <br/><br/>This project integrates biomechanical modeling, kinematics from high-speed videos, and phylogenetic comparative methods to understand the evolution of form-function relationships and their impact on macroevolution of morphology and swimming performance in anurans. The project has three key aims. In Aim 1 the PI will examine the evolution of allometry in locomotor morphology, highlighting how to leverage phylogenetic comparative methods to best estimate interspecific allometric scaling exponents. In Aim 2, he will address the mechanics and scaling of swimming in anurans. He will develop and empirically test a mathematical model of the complete swimming stroke in frogs, then use the model and phylogenetic comparative methods to explain the scaling between peak swimming velocity and body mass. In Aim 3, the PI will examine the sensitivity of swimming performance to different morphological variables through both mathematical and statistical modeling, and he will test the tempo and mode of morphological and swimming performance evolution as a function of mechanical sensitivity. The intellectual merit of the project primarily stems from integrating disparate methods (experiments, mathematical modeling, phylogenetic analyses) and providing an evolutionary comparative framework for testing general physical principles and their influence on the macroevolution of form and function. The broader impacts of the project will result from developing secondary education in scientific research and evolutionary concepts in the PI's state, integrating research training into undergraduate laboratories, and training young researchers in biomechanics in phylogenetic comparative methods workshops. <br/><br/>This project is jointly funded by the Physiological Mechanisms and Biomechanics Program of BIO-Integrative Organismal Systems and the Established Program to Support Competitive Research (EPSCoR).<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
05/29/2024
|
08/07/2024
|
None
|
Grant
|
47.074, 47.083
|
1
|
4900
|
4900
|
2430681
|
{'FirstName': 'Daniel', 'LastName': 'Moen', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Daniel S Moen', 'EmailAddress': '[email protected]', 'NSF_ID': '000519836', 'StartDate': '05/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-Riverside', 'CityName': 'RIVERSIDE', 'ZipCode': '925210001', 'PhoneNumber': '9518275535', 'StreetAddress': '200 UNIVERSTY OFC BUILDING', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '39', 'CONGRESS_DISTRICT_ORG': 'CA39', 'ORG_UEI_NUM': 'MR5QC5FCAVH5', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF CALIFORNIA AT RIVERSIDE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-Riverside', 'CityName': 'RIVERSIDE', 'StateCode': 'CA', 'ZipCode': '925210001', 'StreetAddress': '200 UNIVERSTY OFC BUILDING', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '39', 'CONGRESS_DISTRICT_PERF': 'CA39'}
|
[{'Code': '765800', 'Text': 'Physiol Mechs & Biomechanics'}, {'Code': '915000', 'Text': 'EPSCoR Co-Funding'}]
|
['2020~131947', '2023~180476', '2024~187839']
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430681.xml'}
|
EAGER: TaskDCL: Building Human Trust in Autonomous Social Navigation With Egocentric Visual Feedback
|
NSF
|
09/15/2024
|
08/31/2026
| 299,954 | 299,954 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Alex Leonessa', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922633'}
|
This EArly-concept Grant for Exploratory Research (EAGER) project aims to advance our understanding of customizing safe control strategies for Autonomous Mobility Systems (AMS) interacting with humans, thereby fostering scientific progress and national prosperity. Safety, crucial for AMS operating alongside people in environments like autonomous cars, wheelchairs, and delivery carts, varies among individuals, influencing their perception of safety risks. Misalignment between onboard safety protocols and human safety sensitivities can erode trust in AMS capabilities. This award supports fundamental research to enhance trust in AMS by using human egocentric eyeglasses, with the frame of reference defined from the users perspective, as external AMS sensors. This approach dynamically creates personalized safety models, adjusting AMS movements to align with estimated sensitivities. By better addressing user safety preferences, AMS technologies can gain broader public acceptance and trust. The societal impact extends across various sectors, ensuring efficient, safe transport in human-shared environments—from logistics to healthcare, enhancing mobility independence. This research also promotes inclusivity by involving underrepresented groups and fosters collaboration between egocentric vision and robotics communities.<br/><br/>AMS requires a choice of safety model and associated parameters to ensure the plans and controls executed will avoid collision with obstacles, such as other humans. However, each individual interacting with the AMS has different safety preferences. This EArly-concept Grant for Exploratory Research (EAGER) project will consider (i) a computer vision model to identify safety risks in the environment based on an individual’s eye-gaze information, (ii) an online inference approach using egocentric visual feedback to estimate the individual’s safety preference, and (iii) a technique to synthesize empathetically astute AMS motions that adapt to those preferences, such as proactively yielding to accommodate a more cautious individual. The research team will demonstrate the efficacy of the approach on an autonomous wheelchair platform and evaluate the connection between empathetic astute motions and trust in AMS capabilities.<br/><br/>This EAGER award has been co-funded by the Dynamics, Controls, and System Diagnostics and the Mind, Machine, and Motor Nexus Programs.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/09/2024
|
08/09/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430686
|
[{'FirstName': 'Anat', 'LastName': 'Caspi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Anat Caspi', 'EmailAddress': '[email protected]', 'NSF_ID': '000652733', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Karen', 'LastName': 'Leung', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Karen Leung', 'EmailAddress': '[email protected]', 'NSF_ID': '000923894', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'ZipCode': '981951016', 'PhoneNumber': '2065434043', 'StreetAddress': '4333 BROOKLYN AVE NE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Washington', 'StateCode': 'WA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'WA07', 'ORG_UEI_NUM': 'HD1WMN6945W6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WASHINGTON', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'StateCode': 'WA', 'ZipCode': '981951016', 'StreetAddress': '4333 BROOKLYN AVE NE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Washington', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'WA07'}
|
[{'Code': '058Y00', 'Text': 'M3X - Mind, Machine, and Motor'}, {'Code': '756900', 'Text': 'Dynamics, Control and System D'}]
|
2024~299954
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430686.xml'}
|
EAGER: Investigation of Deviation as the Second Optimization Signal (SOS) for Classification in Ensemble Learning
|
NSF
|
01/01/2025
|
12/31/2026
| 299,883 | 299,883 |
{'Value': 'Standard Grant'}
|
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
|
{'SignBlockName': 'Hector Munoz-Avila', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924481'}
|
This project is motivated by the way humans learn when collaborating. Collaboration between skilled human learners with diverse backgrounds is a primary way that new knowledge is generated when ground-truth information is not available. Collaborating learners should be skilled so that their contributions to the group are sound. The requirement that the set of learners is diverse is premised on the idea that the individual contributions of a single learner may shine light on things not known by another. For example, in cutting-edge scientific research, this situation arises when there is no known solution to a challenging problem. If an individual researcher cannot make progress, the researcher will tend to exchange ideas and collaborate with other researchers (sometimes from different disciplines). In this collaborative ensemble learning setting, individual learners inspire and gain knowledge from each other. We aim to do the same in this research for learning algorithms working together to solve problems. This project will directly promote undergraduate and graduate research and training; encourage participation from women and members of underrepresented groups; and impact Computer Science (CS) and non-CS curricula and courseware broadly and sustainably.<br/><br/>This project aims to emulate the benefits that a group of learners may get from collaboratively solving a problem together by learning from their combined output. The combination of pre-trained model outputs—a practice known as ensemble learning—has been well founded in methods like Bagging and Bayesian Model Averaging as a way to mitigate errors of component models. However, compared to the dynamic, mutually inspiring, and individually beneficial human collaboration process, current ensemble learning methods such as majority voting are often static and used as a last-step “one-time deal” for a small performance boost. The main idea of this work is that given a set of diverse pre-trained classifiers, their ensemble combined output can be a form of pseudo-label that the individual classifiers can learn from. These pseudo-labels can serve as a secondary optimization signal, especially when the primary ground-truth label signal is unavailable. The overall goal of this project is to use the diversity of knowledge present across a set of pre-trained models to compensate for the bias of any particular model and reduce average generalization error of all member models in the process. Additionally, if our ensemble prediction is given by the sample average over member model outputs, then our approach reduces the variation of the learning method by a factor of the number of models used in the ensemble and reduces the overall generalization error in the bias-variance decomposition of the ensemble expected test error. This project will provide important insights to both human learning (that is, education) and machine learning (for approaches such as Mixtures of Experts) with respect to multiple learning agents/models, with the benefits of improving not only overall performance, but also individual performance of participating models.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/30/2024
|
07/30/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430699
|
{'FirstName': 'Wei', 'LastName': 'Ding', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Wei Ding', 'EmailAddress': '[email protected]', 'NSF_ID': '000518968', 'StartDate': '07/30/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Massachusetts Boston', 'CityName': 'DORCHESTER', 'ZipCode': '021253300', 'PhoneNumber': '6172875370', 'StreetAddress': '100 WILLIAM T MORRISSEY BLVD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_ORG': 'MA08', 'ORG_UEI_NUM': 'CGCDJ24JJLZ1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MASS AT BOSTON', 'ORG_PRNT_UEI_NUM': 'CGCDJ24JJLZ1'}
|
{'Name': 'University of Massachusetts Boston', 'CityName': 'DORCHESTER', 'StateCode': 'MA', 'ZipCode': '021253300', 'StreetAddress': '100 WILLIAM T MORRISSEY BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_PERF': 'MA08'}
|
{'Code': '736400', 'Text': 'Info Integration & Informatics'}
|
2024~299883
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430699.xml'}
|
CIVIC-PG Track A: Create an Ethical Urban Digital Twin to Co-design Heat Mitigations for Integrated Indoor and Outdoor Environments
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Daan Liang', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922441'}
|
The objective of this Civic Innovation Challenge (CIVIC) project is to support research focused on designing and piloting an Ethical Urban Digital Twin (EUDT) tailored for San Antonio's Westside neighborhood — a historically disadvantaged Hispanic community. Collaboration between the University of Texas at San Antonio, Texas A&M University, the Historic Westside Residents Association, and the City of San Antonio seeks to provide holistic solutions to mitigate heat-related problems. With rising temperatures, measures like enhanced insulation, air conditioning, and natural ventilation are crucial to individuals’ health. However, past studies often investigate indoor or outdoor spaces separately, overlooking the inherent connection between the two and limiting the offering of integrated solutions. While digital twin holds promise to bridge the gap between indoor and outdoor spaces for thermal comfort evaluation, they generates ethical concerns related to privacy, transparency, and fairness that might lead to undue burden on disadvantaged communities. The broader significance of this research project lies in its potential to serve as a scalable model for aiding other communities facing similar socioeconomic and climate challenges.<br/><br/>In Stage 1, the research project centers on building an Ethical Urban Digital Twin for disadvantaged communities to mitigate heat risk. Academic partners will use privacy-preserving sensors and algorithms to prototype digital twin models of indoor and outdoor environments for homes, offices, and businesses. Low-cost PurpleAir sensors will be installed to gather real-time microclimate data, leveraging past work and existing assets in the Westside neighborhood. Community engagement will involve workshops and interactive sessions with residents and stakeholders to co-design the EUDT and address ethical concerns. The integrated models intend to enable simulation of various environmental scenarios to assess thermal comfort and identify effective mitigation strategies. The anticipated outcomes of this research include: (1) an integrated indoor and outdoor digital twin prototype powered by real-time environmental sensors; (2) community feedback on the ethics of digital twin prototype and the feasibility of risk mitigation solutions; (3) a Stage 2 work plan ready for immediate implementation.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430700
|
[{'FirstName': 'Xinyue', 'LastName': 'Ye', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xinyue Ye', 'EmailAddress': '[email protected]', 'NSF_ID': '000645167', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ryun Jung', 'LastName': 'Lee', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ryun Jung Lee', 'EmailAddress': '[email protected]', 'NSF_ID': '000835753', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Wei', 'LastName': 'Zhai', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Wei Zhai', 'EmailAddress': '[email protected]', 'NSF_ID': '000909794', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Peyman', 'LastName': 'Najafirad', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Peyman Najafirad', 'EmailAddress': '[email protected]', 'NSF_ID': '000662068', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Esteban', 'LastName': 'Lopez Ochoa', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Esteban A Lopez Ochoa', 'EmailAddress': '[email protected]', 'NSF_ID': '000879376', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Texas at San Antonio', 'CityName': 'SAN ANTONIO', 'ZipCode': '782491644', 'PhoneNumber': '2104584340', 'StreetAddress': '1 UTSA CIR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '20', 'CONGRESS_DISTRICT_ORG': 'TX20', 'ORG_UEI_NUM': 'U44ZMVYU52U6', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY OF TEXAS AT SAN ANTONIO', 'ORG_PRNT_UEI_NUM': 'X5NKD2NFF2V3'}
|
{'Name': 'University of Texas at San Antonio', 'CityName': 'SAN ANTONIO', 'StateCode': 'TX', 'ZipCode': '782491644', 'StreetAddress': '1 UTSA CIR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '20', 'CONGRESS_DISTRICT_PERF': 'TX20'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430700.xml'}
|
EAGER: PBI: Designing Public Use Microdata Business Areas (PUMBAs) for Innovation
|
NSF
|
10/01/2024
|
09/30/2026
| 299,999 | 299,999 |
{'Value': 'Standard Grant'}
|
{'Code': '15020000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'ITE', 'LongName': 'Innovation and Technology Ecosystems'}}
|
{'SignBlockName': 'Rebecca Shearman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927403'}
|
Currently, there is unprecedented investment in regional and place-based innovation ecosystems through programs such as the National Science Foundation’s Regional Innovation Engines (hereafter, NSF Engines), the Economic Development Administration’s Tech Hubs, and the U.S. Department of Energy’s Hydrogen Hubs. A key constraint from a program evaluation perspective is the lack of regional and place-based baseline data against which to measure societal and economic impact (e.g., number and share of companies that currently conduct research and development (R&D); number and share of companies that report innovation activity; ownership of firms by sex, ethnicity, race, and veteran status). This project seeks to develop and validate a process for generating new geographic subdivisions well-suited for business microdata such as the Annual Business Survey (ABS). This would be analogous to the Public Use Microdata Areas (PUMAs) developed by the Census Bureau for the American Community Survey (ACS). Release of geographic definitions of these regions and related microdata or summary statistics will allow researchers and policymakers access to these data for place-based innovation.<br/><br/>Geographic clustering is an open-ended problem. In general, finding an optimal solution is infeasible, because it requires investigating all possible cluster sizes and memberships. Several reasonable and efficient approaches exist in the literature and in open-source code; however, different algorithms may lead to different use cases being either strongly or poorly supported. Use of synthetic microdata is also an open-ended problem. Similarly, many general approaches exist but need to be evaluated for appropriateness of use cases. Finally, research on both methods has tended to focus on data for individuals rather than establishments (businesses). Adapting evaluation metrics for utility and disclosure risk to these units of analysis will expand the methodology in this area. This work will use a motivating application based on demographics of business ownership and innovation rates for businesses to further our understanding in each of these three areas: clustering algorithms, synthetic data methods, and evaluation metrology.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/09/2024
|
07/09/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2430732
|
[{'FirstName': 'Christine', 'LastName': 'Task', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christine M Task', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A03T7', 'StartDate': '07/09/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jennifer', 'LastName': 'Ozawa', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jennifer K Ozawa', 'EmailAddress': '[email protected]', 'NSF_ID': '000905973', 'StartDate': '07/09/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Matthew', 'LastName': 'Williams', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Matthew R Williams', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A02XN', 'StartDate': '07/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Research Triangle Institute', 'CityName': 'DURHAM', 'ZipCode': '277090155', 'PhoneNumber': '9195416000', 'StreetAddress': '3040 CORNWALLIS RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'NC04', 'ORG_UEI_NUM': 'JJHCMK4NT5N3', 'ORG_LGL_BUS_NAME': 'RESEARCH TRIANGLE INSTITUTE', 'ORG_PRNT_UEI_NUM': 'JJHCMK4NT5N3'}
|
{'Name': 'Research Triangle Institute', 'CityName': 'Research Triangle Park', 'StateCode': 'NC', 'ZipCode': '277092194', 'StreetAddress': '3040 East Cornwallis Rd', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'NC04'}
|
{'Code': '301Y00', 'Text': 'NSF Engines - Type 2'}
|
2024~299999
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430732.xml'}
|
NLI: Research: Integrating Sustainability into Industrial and Systems Engineering Curriculum
|
NSF
|
09/01/2024
|
08/31/2027
| 350,000 | 350,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07050000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'EEC', 'LongName': 'Div Of Engineering Education and Centers'}}
|
{'SignBlockName': 'Matthew A. Verleger', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922961'}
|
Social and environmental sustainability is key to human and environmental well-being, both now and in the future. Engineers have an ethical responsibility to consider the social and environmental impact of their designs. Engineering education plays a vital role in shaping future engineers equipped to tackle sustainability challenges. Traditionally, sustainability has been taught merely as a skill or topic, but this approach is no longer sufficient. A systems approach is needed to integrate sustainability into engineering courses. This project will examine how integrating sustainability, particularly environmental and social sustainability, into Industrial and Systems Engineering (ISE) can enhance student learning and prepare them to become professional engineers capable of addressing sustainability challenges in complex system. It aligns well with the NSF-Lemelson Initiative on Environmental and Social Sustainability in Engineering Education.<br/><br/>The specific objectives of this project include: (1) integrating sustainability into various ISE courses at North Carolina A&T State University (NCA&T) using the Engineering for One Planet (EOP) framework, (2) preparing course materials for sustainability following the design-based engineering learning (DBEL) model, (3) conducting research on student learning using data collected from the courses, including pre- and post-tests, log files, formative and summative assessments, and self-reports using questionnaires, and (4) developing and implementing a course material transferability plan to broaden the impact of this project beyond ISE and NCA&T. This project will integrate sustainability into ten critical ISE courses spanning from freshman to senior year. Students will progressively learn sustainability concepts, theories, and tools throughout their academic journey. Each course will be revised, and student learning outcomes from the EOP framework will be implemented. This project will adopt DBEL to teach students sustainability concepts and tools. Two application areas—manufacturing and hunger relief—will be used to develop design problems that address social and environmental sustainability. This project will also identify and address critical challenges in integrating sustainability into the ISE curriculum. The findings of this project will significantly contribute to the knowledge base regarding innovative pedagogies for integrating sustainability. It will address questions such as how EOP can be applied to ISE courses and how effective these applications are. The research outcomes will provide engineering educators with a roadmap to integrate sustainability into their curriculum. This research will provide substantial benefits to the environment and society by preparing the next generation of engineers to tackle environmental and social sustainability issues, thereby improving human and environmental well-being. By adopting a systems approach to integrating sustainability into the curriculum, graduates will become ethically responsible engineers, equipped with the necessary knowledge and skills to design for a better future planet. Given that African Americans are underrepresented in engineering and disproportionately affected by environmental and social impacts, this research will help cultivate a large number of African American engineers passionate about generating effective and innovative designs to address sustainability challenges and improve social and environmental justice. The results of this project will be disseminated through a web portal, where course materials, design problems, and project ideas will be shared with the engineering education community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/07/2024
|
08/07/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430739
|
[{'FirstName': 'Paul', 'LastName': 'Stanfield', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Paul M Stanfield', 'EmailAddress': '[email protected]', 'NSF_ID': '000254226', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Steven', 'LastName': 'Jiang', 'PI_MID_INIT': 'X', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Steven X Jiang', 'EmailAddress': '[email protected]', 'NSF_ID': '000493859', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Lauren', 'LastName': 'Davis', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lauren Davis', 'EmailAddress': '[email protected]', 'NSF_ID': '000064815', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Vernal', 'LastName': 'Alford', 'PI_MID_INIT': None, 'PI_SUFX_NAME': 'III', 'PI_FULL_NAME': 'Vernal Alford', 'EmailAddress': '[email protected]', 'NSF_ID': '000630200', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Muyue', 'LastName': 'Han', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Muyue Han', 'EmailAddress': '[email protected]', 'NSF_ID': '000996025', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'North Carolina Agricultural & Technical State University', 'CityName': 'GREENSBORO', 'ZipCode': '274110002', 'PhoneNumber': '3363347995', 'StreetAddress': '1601 E MARKET ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'NC06', 'ORG_UEI_NUM': 'SKH5GMBR9GL3', 'ORG_LGL_BUS_NAME': 'NORTH CAROLINA AGRICULTURAL AND TECHNICAL STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'North Carolina Agricultural & Technical State University', 'CityName': 'GREENSBORO', 'StateCode': 'NC', 'ZipCode': '274110002', 'StreetAddress': '1601 E MARKET ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'NC06'}
|
{'Code': '134000', 'Text': 'EngEd-Engineering Education'}
|
2024~350000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430739.xml'}
|
3D DNA Spectroscopic Photon-Localization Intrinsic-Contrast Nanoscopy
|
NSF
|
09/01/2024
|
08/31/2027
| 649,999 | 649,999 |
{'Value': 'Standard Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Adam Wax', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928809'}
|
Super-resolution microscopy has revolutionized the study of biology, but crucial technical barriers remain to image cells in 3D at the extremely small length scales needed to understand the fundamental structure and function of the genome, such as double-strand DNA. Current imaging techniques require the use of fluorescent labels which can disrupt natural cellular processes, presenting a challenge for understanding how the molecular machinery underpinning cellular behavior and many disease processes operates. This project will develop a new label-free nanoimaging platform to image the genome of intact fixed cells in 3D, with 2 nanometer resolution while providing chemical and molecular information, along with comprehensive structural and functional information. This may lead to a deeper understanding of the 3D structure of cells in their natural state and eventually to better understanding of multiple significant disease processes at the fundamental molecular level. In addition, the project will provide training and educational opportunities to a diverse audience through public symposia and workshops, mentorship, outreach to K-12 students, and by recruiting undergraduate students from minority-serving institutions in the Chicago region who may not have the opportunity to gain exposure or access to cutting-edge scientific research projects.<br/><br/>This project will develop a new label-free nanoimaging platform, 3D DNA spectroscopic photon-localization intrinsic-contrast nanoscopy (3D DNA-SPIN), to image chromatin in 3D in intact fixed cells with 2 nm resolution while providing chemical and molecular information. Bringing the spatial resolution below 10 nm would enable imaging of chromatin at the nucleosomal scale. Enhancing resolution to ~2 nm would allow thus far unattainable imaging of chromatin at its most fundamental level, the double-strand DNA. If developed, this technique may answer the long-standing question of the 3D conformation of the chromatin polymer in its native state. The ability to record stochastic excitation-emission spectra will increase the spatial resolution of DNA localization and provide chemico-functional information about emitting DNA such as nucleotide sequences. Finally, 3D DNA-SPIN will be co-registered with existing single molecule localization microscopy (SMLM) modalities for superresolution molecular imaging of histone states, polymerases, locations of specific genes, and other molecular events, together providing comprehensive structural, functional, and molecular information, which in the longer term may help elucidate the interplay between chromatin, epigenetics, and phenotype. This project aims to 1) develop 3D DNA-SPIN for 3D imaging of cells with spatial resolution approaching 2 nm, 2) characterize photophysical properties of label-free, endogenous DNA photoswitching, and 3) develop and validate algorithms for molecular recognition using 3D DNA-SPIN. Based on the photochemical characterization in the second aim, machine/deep learning algorithms will be developed to use DNA-SPIN emission-excitation data to distinguish nucleotide sequences, including AT- versus CG-rich parts of the genome, which are mostly associated with repressed vs gene-rich parts of the genome. The project will also explore the feasibility of generating other functional data including DNA and nucleosomal conformations, volume concentration, and surrounding ionic environment. Cross-validation experiments on fixed cells will be performed to verify the accuracy, reliability, and robustness of the algorithm. In addition, the project will provide training and educational opportunities to a diverse audience through public symposia and workshops, mentorship, outreach to K-12 students, and by recruiting undergraduate students from<br/>minority-serving institutions in the Chicago region who may not have the opportunity to have exposure or access to cutting-edge scientific research projects.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/01/2024
|
08/01/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430743
|
[{'FirstName': 'Vadim', 'LastName': 'Backman', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Vadim Backman', 'EmailAddress': '[email protected]', 'NSF_ID': '000188997', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Geng', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Geng Wang', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A04DD', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Northwestern University', 'CityName': 'EVANSTON', 'ZipCode': '602080001', 'PhoneNumber': '3125037955', 'StreetAddress': '633 CLARK ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'IL09', 'ORG_UEI_NUM': 'EXZVPWZBLUE8', 'ORG_LGL_BUS_NAME': 'NORTHWESTERN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Northwestern University', 'CityName': 'EVANSTON', 'StateCode': 'IL', 'ZipCode': '602080001', 'StreetAddress': '633 CLARK ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'IL09'}
|
{'Code': '723600', 'Text': 'BioP-Biophotonics'}
|
2024~649999
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430743.xml'}
|
Collaborative Research: CISE MSI: RCBP: SCH: Advancing Breast-Cancer Detection in Ultrasound Imaging through Active- and Weakly-Supervised Learning
|
NSF
|
09/01/2024
|
08/31/2026
| 203,981 | 203,981 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'James Fowler', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928910'}
|
Early detection of breast cancer is critical to decreasing mortality, and breast-ultrasound imaging is commonly employed in early diagnosis due to its widespread availability, portability, and affordability. Yet, breast ultrasound is inherently noisy and of low contrast, characteristics that challenge its effectiveness at breast-cancer diagnosis and hinder application of automated deep-learning methods. Furthermore, the training such state-of-the-art deep learning requires extensive training samples equipped with costly manual labeling by radiologists. Therefore, this project aims to develop breast-cancer detection using deep learning that can function effectively with minimal annotations as well as within the substantial noise inherent to breast ultrasound. Beyond boosting public-health outcomes, broader-impact activities include the participation of women and minority students in the research. <br/><br/>Specifically, this project aims to develop a weakly-supervised breast-cancer detection using active and weakly-supervised learning to help doctors diagnose breast cancer in ultrasound images. Weakly-supervised object localization will be applied to avoid reliance on bounding-box-level annotations, instead employing a transformer-based classification network to detect breast cancer. Furthermore, active learning will select the most informative images for training an improved breast-cancer detection model by iteratively choosing the most relevant breast-ultrasound images based on detection outcomes to successively refine the model's capabilities. The success of this project will bring both social and technological benefits, its outcomes enhancing women's health by assisting early detection of breast cancer, particularly benefiting underrepresented groups.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/01/2024
|
08/01/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430746
|
[{'FirstName': 'Kuan', 'LastName': 'Huang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kuan Huang', 'EmailAddress': '[email protected]', 'NSF_ID': '000950965', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Meng', 'LastName': 'Xu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Meng Xu', 'EmailAddress': '[email protected]', 'NSF_ID': '000988074', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Kean University', 'CityName': 'UNION', 'ZipCode': '070837133', 'PhoneNumber': '9083733464', 'StreetAddress': '1000 MORRIS AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'NJ10', 'ORG_UEI_NUM': 'SQ62WM5KNSV8', 'ORG_LGL_BUS_NAME': 'KEAN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Kean University', 'CityName': 'UNION', 'StateCode': 'NJ', 'ZipCode': '070837133', 'StreetAddress': '1000 MORRIS AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'NJ10'}
|
{'Code': '173Y00', 'Text': 'CISE MSI Research Expansion'}
|
2024~203981
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430746.xml'}
|
Collaborative Research: CISE MSI: RCBP: SCH: Advancing Breast-Cancer Detection in Ultrasound Imaging through Active- and Weakly-Supervised Learning
|
NSF
|
09/01/2024
|
08/31/2026
| 195,000 | 195,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'James Fowler', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928910'}
|
Early detection of breast cancer is critical to decreasing mortality, and breast-ultrasound imaging is commonly employed in early diagnosis due to its widespread availability, portability, and affordability. Yet, breast ultrasound is inherently noisy and of low contrast, characteristics that challenge its effectiveness at breast-cancer diagnosis and hinder application of automated deep-learning methods. Furthermore, the training such state-of-the-art deep learning requires extensive training samples equipped with costly manual labeling by radiologists. Therefore, this project aims to develop breast-cancer detection using deep learning that can function effectively with minimal annotations as well as within the substantial noise inherent to breast ultrasound. Beyond boosting public-health outcomes, broader-impact activities include the participation of women and minority students in the research. <br/><br/>Specifically, this project aims to develop a weakly-supervised breast-cancer detection using active and weakly-supervised learning to help doctors diagnose breast cancer in ultrasound images. Weakly-supervised object localization will be applied to avoid reliance on bounding-box-level annotations, instead employing a transformer-based classification network to detect breast cancer. Furthermore, active learning will select the most informative images for training an improved breast-cancer detection model by iteratively choosing the most relevant breast-ultrasound images based on detection outcomes to successively refine the model's capabilities. The success of this project will bring both social and technological benefits, its outcomes enhancing women's health by assisting early detection of breast cancer, particularly benefiting underrepresented groups.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/01/2024
|
08/01/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430747
|
{'FirstName': 'Yingfeng', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yingfeng Wang', 'EmailAddress': '[email protected]', 'NSF_ID': '000709176', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Tennessee Chattanooga', 'CityName': 'CHATTANOOGA', 'ZipCode': '374032504', 'PhoneNumber': '4234254431', 'StreetAddress': '615 MCCALLIE AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Tennessee', 'StateCode': 'TN', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'TN03', 'ORG_UEI_NUM': 'JNZFHMGJN7M3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF TENNESSEE', 'ORG_PRNT_UEI_NUM': 'RZ1YV5AUBN39'}
|
{'Name': 'University of Tennessee Chattanooga', 'CityName': 'CHATTANOOGA', 'StateCode': 'TN', 'ZipCode': '374032504', 'StreetAddress': '615 MCCALLIE AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Tennessee', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'TN03'}
|
{'Code': '173Y00', 'Text': 'CISE MSI Research Expansion'}
|
2024~195000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430747.xml'}
|
C2H2 EAGER: Exploring Climate Drivers of Traditional Food Intake in Alaska Native Communities
|
NSF
|
08/15/2024
|
07/31/2026
| 300,000 | 300,000 |
{'Value': 'Standard Grant'}
|
{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}
|
{'SignBlockName': 'Barbara Ransom', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927792'}
|
Indigenous peoples in Alaska are among our nation’s most vulnerable populations. They are affected cumulatively and disproportionately by structural, societal, and geophysical determinants of health. Alaska Native health and well-being is tied to the land and environment. In rural Alaskan Native communities, for which a subsistence lifestyle is a nutritional imperative as well as a cultural and spiritual anchor. As a result, changes in the environment deeply impact their physical and mental health. This research addresses how climate change has resulted in changes to traditional food intake that has in turn impacted the health and welfare of Alaskan Native people. The impacts of long-term and short-term climate variation on subsistence activity have been well-documented in surveys and interviews with Indigenous communities. This research provides complementary evidence for historical relationships that are otherwise challenging to analyze due to lack of data. The project does this by including geoscience parameters, engaging geoscientists in the research, and examining geoscience principles related to critical climate variables related to subsistence food sources. These parameters include temperature, sea ice extent, precipitation, and others as documented over decades-long time frames. Alaskan Native diet indicators will be determined from data from blood samples of Native Alaskans that reside in Alaskan public health archives. Broader impacts of the work include environmental justice and equity understandings of native Alaskan communities that build on unique data sources and access to new expertise and well developed Alaskan Native community relationships. Results of the research will have implications for health equity in the face of climate change across Alaska.<br/><br/>This exploratory study seeks to develop novel, climate change, and human health indicator models demonstrating the longitudinal linkages between climatic variables and traditional food consumption in rural Alaskan Native communities. The research involves an expert interdisciplinary team, based out of the University of Alaska Fairbanks which is an institution in an EPSCoR state. The team expertise covers various fields and has representation from geoscientists, nutrition biologists, and medical/public health professionals. The work integrates western knowledge and approaches with Alaskan Native Indigenous knowledge and interaction with Native Alaskans. Researchers at the Alaska Center for Climate Assessment and Policy are responsible for modeling climate variables at the regional and subregional scale, including monthly temperature, precipitation, and sea ice extent, as well as the annual timing of river ice break-up. Data, over multiple decades, will be examined (i.e., from the 1970s through the 2010s) for a number of rural Alaskan Native communities. Researchers from the Center for Alaska Native Health Research are responsible for identifying dietary transitions in rural Indigenous communities using natural-abundance, stable isotope, and biomarkers in blood serum samples archived at the Alaska Area Specimen Bank over the time period of investigation. Modeling of longitudinal trends in traditional food intake include comparison with changes in climatic variables and community geography (coastal vs. up-river) and seasonality of traditional diets. The research team, with guidance from Alaskan Native community members, will identify extreme weather and seasonal events with significant historical impact on subsistence harvesting activities. Short-term impacts in traditional food intake will also be examined. Exploring climate drivers of traditional food intake over time could transform our current knowledge, policies, and practices for natural resource management in Alaska by examining the linked aspects of human health impacts to climate change. The research team's long-time engagement with Alaskan Native communities makes it well-positioned to interact effectively with Native communities and able carry out the work proposed. This novel, transdisciplinary approach lays the groundwork for other studies to improve our knowledge of the diet and health of indigenous Alaskan communities and their tie to climate change.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/04/2024
|
08/04/2024
|
None
|
Grant
|
47.050
|
1
|
4900
|
4900
|
2430753
|
{'FirstName': 'Stacy', 'LastName': 'Rasmus', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Stacy M Rasmus', 'EmailAddress': '[email protected]', 'NSF_ID': '000556049', 'StartDate': '08/04/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Alaska Fairbanks Campus', 'CityName': 'FAIRBANKS', 'ZipCode': '997750001', 'PhoneNumber': '9074747301', 'StreetAddress': '2145 N TANANA LOOP', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Alaska', 'StateCode': 'AK', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'AK00', 'ORG_UEI_NUM': 'FDLEQSJ8FF63', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ALASKA FAIRBANKS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Alaska Fairbanks Campus', 'CityName': 'FAIRBANKS', 'StateCode': 'AK', 'ZipCode': '997757880', 'StreetAddress': '2145 N TANANA LOOP', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Alaska', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'AK00'}
|
{'Code': '300Y00', 'Text': 'Climate Impact on Human Health'}
|
2024~300000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430753.xml'}
|
C2H2 RCN: OneEarth OneHealth: An Ecosystem for Human-Centered Climate Solutions
|
NSF
|
09/01/2024
|
08/31/2029
| 500,000 | 500,000 |
{'Value': 'Standard Grant'}
|
{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}
|
{'SignBlockName': 'Barbara Ransom', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927792'}
|
This Research Coordination Network will establish a framework for innovative human-centered solutions and implementation strategies to reduce the impacts of climate change on human health. The network will advance a new science, called GeoHealth, that has been established by a community of researchers who study the interconnections between earth processes and human health. Goals of these activities range from studying climate change impacts on human health to finding science-based and human-centered implementable solutions. The network provides participants with training and skills to co-design, between geoscientists and medical/health professionals, human-centered solutions that cross the boundaries of traditional medical and non-medical scientific disciplines. Network participants will collaborate to combine their knowledge, expertise, tools, and data to address, in a holistic manner, a panoply of serious climate-driven health impacts that take into account that fact that the earth system is not compartmentalized but where all components are inextricably intertwined. Broader impacts of the work include training members in community engagement and leadership as well as in team science and developing skills to effectively interact with the public and with decision and policy makers seeking science-based input to improve public health and well being that is grounded in fact. <br/><br/>The One-Earth One-Health Research Coordination Network, which involves participants across the geosciences and health professions, is based on the foundation that all earth processes directly or indirectly influence human health in the short- and long-term. Goals are to create human-centered, implementable solutions that are science-based and increase recognition of the medical profession of the importance of working with and engaging <br/>geoscientists who study the environment and the environmental triggers that cause serious human health conditions. Such a collaboration is essential if a holistic, preventive approach to solving serious health issues is to be achieved. Because geoscientists are generally trained to solve problems that involve long time-scales and medical professionals undergo almost exclusively patient-centric training, the two fields - both of which are essential for a complete understanding of both the environmental trigger and its manifestation in the human body, have not worked closely with each other. This research network was created to change that. As the climate changes, our adaptation to it and solutions devised to prevent or mitigate or otherwise protect human health require geoscientists be trained, work with, and communicate effectively to health scientists, policymakers, and the public. The One-Earth One-Health Research network will devise an online curriculum on team science, provide a platform for the synthesis of knowledge on climate change impacts on human health, work to develop human-centered solutions to climate-driven climate health issues, design solution implementation strategies, create communication strategies, and establish GeoHealth curriculum that can be used as part of the university curriculum in geoscience.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/21/2024
|
08/21/2024
|
None
|
Grant
|
47.050
|
1
|
4900
|
4900
|
2430762
|
{'FirstName': 'Thanh', 'LastName': 'Nguyen', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Thanh H Nguyen', 'EmailAddress': '[email protected]', 'NSF_ID': '000304927', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Illinois at Urbana-Champaign', 'CityName': 'URBANA', 'ZipCode': '618013620', 'PhoneNumber': '2173332187', 'StreetAddress': '506 S WRIGHT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'IL13', 'ORG_UEI_NUM': 'Y8CWNJRCNN91', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ILLINOIS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Illinois at Urbana-Champaign', 'CityName': 'URBANA', 'StateCode': 'IL', 'ZipCode': '618013620', 'StreetAddress': '506 S WRIGHT ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_PERF': 'IL13'}
|
[{'Code': '300Y00', 'Text': 'Climate Impact on Human Health'}, {'Code': '722200', 'Text': 'XC-Crosscutting Activities Pro'}]
|
2024~500000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430762.xml'}
|
CIVIC-PG Track B: A Collect-Relay-Deliver Model for Creating Food-Secure Aging Communities
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Daan Liang', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922441'}
|
The objective of this Civic Innovation Challenge (CIVIC) project is to support research on developing, piloting, and evaluating CORELADE, a novel home delivery model that COllects, RELAys, and DElivers surplus food to food-insecure aging communities through nonprofit organizations. By 2050, 20% (or 84 million) of the U.S. population will reach the age of 65. As the number of seniors grows, so does the need for food security. The number of food-insecure seniors rose from 4.9 million in 2016 to 5.2 million in 2020 and continues to grow. One solution is to provide home delivery through non-profit organizations. However, while commercial home delivery models have witnessed great success, they do not translate well to the nonprofit sector as volunteers typically find home delivery tasks — the time and costs involved — very demanding. Thus, there is an urgent need to make non-profit organizations’ home delivery models better aligned with capabilities and motivations of volunteer workforce, ensuring that the system is efficient, equitable, and financially sustainable. CORELADE aims to substantially increase seniors’ access to healthy food in the pilot communities, thus improving their quality of life and community wellbeing.<br/><br/>CORELADE research will leverage complementary capabilities of nonprofit organizations’ vehicle fleets and volunteers' personal vehicles for food collection and delivery, with the intent of utilizing strategically located relay stations to reduce the logistical burdens. It draws on theories and methods from behavioral psychology, optimization and data analytics, computing, and community engagement to optimize food collection and delivery plans, thereby minimizing the efforts associated with home delivery. As a result, CORELADE hopes to motivate volunteers to take on home delivery tasks, extend the scope of non-profit home delivery initiatives, and ultimately create food-secure communities for senior population. This project involves academic researchers from Drexel University, Sharing Excess (a non-profit organization Based in Philadelphia, dedicated to ending food insecurity) and two organizations serving aging communities in the Philadelphia region (University Square Apartments and ElderNet). It is expected that CORELADE not only improves Sharing Excess’s operations but also serves as a scalable model for communities across the country.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track B. Bridging the gap between essential resources and services & community needs and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430767
|
[{'FirstName': 'Zhiwei', 'LastName': 'Chen', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zhiwei Chen', 'EmailAddress': '[email protected]', 'NSF_ID': '000927521', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Nourhan', 'LastName': 'Ibrahim', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nourhan Ibrahim', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A03MP', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jillian', 'LastName': 'Hmurovic', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jillian Hmurovic', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A04JM', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Drexel University', 'CityName': 'PHILADELPHIA', 'ZipCode': '191042875', 'PhoneNumber': '2158956342', 'StreetAddress': '3141 CHESTNUT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'PA03', 'ORG_UEI_NUM': 'XF3XM9642N96', 'ORG_LGL_BUS_NAME': 'DREXEL UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Drexel University', 'CityName': 'PHILADELPHIA', 'StateCode': 'PA', 'ZipCode': '191042875', 'StreetAddress': '3141 CHESTNUT ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'PA03'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430767.xml'}
|
Collaborative Research: CISE MSI: RDP: CPS: Biomimetic Swarm-Based Remote Sensing for Inaccessible Environments
|
NSF
|
10/01/2024
|
09/30/2027
| 199,999 | 199,999 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Karl Wimmer', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922095'}
|
This project aims to develop innovative technology for environmental monitoring. The researchers are inspired by the natural design of dandelions to create a swarm of tiny, lightweight sensors that can be deployed in hard-to-reach areas by unmanned aerial vehicles (UAVs). These sensors will harness wind currents to spread across vast and difficult terrains, collecting crucial data on environmental conditions. This technology promises to improve our understanding of ecosystems and aid in disaster management by providing real-time, detailed information in places that are otherwise inaccessible. The project brings together expertise from three institutions and will enhance research capacity, support education, and promote diversity in STEM fields.<br/><br/>The project focuses on developing a biomimetic swarm sensing system that emulates the dispersal method of dandelion seeds. The system includes sensors with pappus-like structures for flight and energy harvesting, and achene-like components for sensing and communication. Key research goals include designing and optimizing the sensor structures for aerodynamic efficiency, developing robust energy harvesting and communication circuits, and creating a transformer-based deep reinforcement learning architecture for autonomous UAV-assisted sensor deployment. The performance of the system will be validated through simulation and experimental testing. This interdisciplinary research integrates aerodynamic analysis, solid mechanics, microelectronics, signal processing, communication theory, and deep reinforcement learning, aiming to advance both basic science and the practical application of biomimetic swarm-based remote sensing technology.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/31/2024
|
07/31/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430771
|
{'FirstName': 'Mostafa', 'LastName': 'Hassanalian', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mostafa Hassanalian', 'EmailAddress': '[email protected]', 'NSF_ID': '000805168', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'New Mexico Institute of Mining and Technology', 'CityName': 'SOCORRO', 'ZipCode': '878014681', 'PhoneNumber': '5758355496', 'StreetAddress': '801 LEROY PL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Mexico', 'StateCode': 'NM', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'NM02', 'ORG_UEI_NUM': 'HZJ2JZUALWN4', 'ORG_LGL_BUS_NAME': 'NEW MEXICO INSTITUTE OF MINING AND TECHNOLOGY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'New Mexico Institute of Mining and Technology', 'CityName': 'SOCORRO', 'StateCode': 'NM', 'ZipCode': '878014681', 'StreetAddress': '801 LEROY PL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Mexico', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'NM02'}
|
{'Code': '173Y00', 'Text': 'CISE MSI Research Expansion'}
|
2024~199999
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430771.xml'}
|
Collaborative Research: CISE MSI: RDP: CPS: Biomimetic Swarm-Based Remote Sensing for Inaccessible Environments
|
NSF
|
10/01/2024
|
09/30/2027
| 200,000 | 200,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Karl Wimmer', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922095'}
|
This project aims to develop innovative technology for environmental monitoring. The researchers are inspired by the natural design of dandelions to create a swarm of tiny, lightweight sensors that can be deployed in hard-to-reach areas by unmanned aerial vehicles (UAVs). These sensors will harness wind currents to spread across vast and difficult terrains, collecting crucial data on environmental conditions. This technology promises to improve our understanding of ecosystems and aid in disaster management by providing real-time, detailed information in places that are otherwise inaccessible. The project brings together expertise from three institutions and will enhance research capacity, support education, and promote diversity in STEM fields.<br/><br/>The project focuses on developing a biomimetic swarm sensing system that emulates the dispersal method of dandelion seeds. The system includes sensors with pappus-like structures for flight and energy harvesting, and achene-like components for sensing and communication. Key research goals include designing and optimizing the sensor structures for aerodynamic efficiency, developing robust energy harvesting and communication circuits, and creating a transformer-based deep reinforcement learning architecture for autonomous UAV-assisted sensor deployment. The performance of the system will be validated through simulation and experimental testing. This interdisciplinary research integrates aerodynamic analysis, solid mechanics, microelectronics, signal processing, communication theory, and deep reinforcement learning, aiming to advance both basic science and the practical application of biomimetic swarm-based remote sensing technology.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/31/2024
|
07/31/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430772
|
{'FirstName': 'Sihua', 'LastName': 'Shao', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sihua Shao', 'EmailAddress': '[email protected]', 'NSF_ID': '000813635', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Colorado School of Mines', 'CityName': 'GOLDEN', 'ZipCode': '804011887', 'PhoneNumber': '3032733000', 'StreetAddress': '1500 ILLINOIS ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Colorado', 'StateCode': 'CO', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'CO07', 'ORG_UEI_NUM': 'JW2NGMP4NMA3', 'ORG_LGL_BUS_NAME': 'TRUSTEES OF THE COLORADO SCHOOL OF MINES', 'ORG_PRNT_UEI_NUM': 'JW2NGMP4NMA3'}
|
{'Name': 'Colorado School of Mines', 'CityName': 'GOLDEN', 'StateCode': 'CO', 'ZipCode': '804011887', 'StreetAddress': '1500 ILLINOIS ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Colorado', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'CO07'}
|
{'Code': '173Y00', 'Text': 'CISE MSI Research Expansion'}
|
2024~200000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430772.xml'}
|
Collaborative Research: CISE MSI: RDP: CPS: Biomimetic Swarm-Based Remote Sensing for Inaccessible Environments
|
NSF
|
10/01/2024
|
09/30/2027
| 200,000 | 200,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Karl Wimmer', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922095'}
|
This project aims to develop innovative technology for environmental monitoring. The researchers are inspired by the natural design of dandelions to create a swarm of tiny, lightweight sensors that can be deployed in hard-to-reach areas by unmanned aerial vehicles (UAVs). These sensors will harness wind currents to spread across vast and difficult terrains, collecting crucial data on environmental conditions. This technology promises to improve our understanding of ecosystems and aid in disaster management by providing real-time, detailed information in places that are otherwise inaccessible. The project brings together expertise from three institutions and will enhance research capacity, support education, and promote diversity in STEM fields.<br/><br/>The project focuses on developing a biomimetic swarm sensing system that emulates the dispersal method of dandelion seeds. The system includes sensors with pappus-like structures for flight and energy harvesting, and achene-like components for sensing and communication. Key research goals include designing and optimizing the sensor structures for aerodynamic efficiency, developing robust energy harvesting and communication circuits, and creating a transformer-based deep reinforcement learning architecture for autonomous UAV-assisted sensor deployment. The performance of the system will be validated through simulation and experimental testing. This interdisciplinary research integrates aerodynamic analysis, solid mechanics, microelectronics, signal processing, communication theory, and deep reinforcement learning, aiming to advance both basic science and the practical application of biomimetic swarm-based remote sensing technology.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/31/2024
|
07/31/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430773
|
{'FirstName': 'Xiang', 'LastName': 'Sun', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xiang Sun', 'EmailAddress': '[email protected]', 'NSF_ID': '000799842', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of New Mexico', 'CityName': 'ALBUQUERQUE', 'ZipCode': '87131', 'PhoneNumber': '5052774186', 'StreetAddress': '1700 LOMAS BLVD NE STE 2200', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Mexico', 'StateCode': 'NM', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NM01', 'ORG_UEI_NUM': 'F6XLTRUQJEN4', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF NEW MEXICO', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of New Mexico', 'CityName': 'ALBUQUERQUE', 'StateCode': 'NM', 'ZipCode': '87131', 'StreetAddress': '1 University of New Mexico', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Mexico', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NM01'}
|
{'Code': '173Y00', 'Text': 'CISE MSI Research Expansion'}
|
2024~200000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430773.xml'}
|
ENG-SEMICON: Coherent Co-packaged Optics (C2PO) using Offset-QAM Modulation
|
NSF
|
09/01/2024
|
08/31/2027
| 422,653 | 422,653 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Ale Lukaszew', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928103'}
|
The advent of computationally intensive applications such as generative artificial intelligence (AI) has created a vital demand for dense and ultra-low power multi-TB/s inter/intra-rack optical communications (with <100m reach) as well as low-latency chip-to-chip interconnects. Similar needs will be soon required for edge-to-cloud connectivity and 5G/6G front/back-haul networks. Silicon photonic (SiPho) Transceivers have shown a great promise to address this challenge by ultimately co-packaging optical transceivers with high performance GPU/FPGA/SoCs in a same package (“co-packaged optics” or CPO). Among various realization approaches, micro-ring modulators (MRM) have significantly improved the energy-efficiency and shoreline (or edge) bandwidth (BW) densities in terms of Tb/s/mm compared with conventional Mach-Zehnder modulators (MZM) and VCSELs. State-of-the-art demonstration could achieve 100Gb/s data-rates per wavelengths with ~5pJ/b energy-efficiencies and less than 0.5Tb/s/mm BW densities using multi-level amplitude modulation. These numbers are still an order of magnitude behind what future AI processing demands. Since there is a large energy penalty in scaling up baud-rates, vast parallelization degrees should be utilized to address multi-TB/s aggregate off-package data-rate demands. So far Wavelength division multiplexing (WDM) have been proposed and demonstrated to do so. While multiplexing can be a near future solutions, it is evident that advanced coherent modulations like QAM can be an ultimate solution to increase spectral-efficiency and overall aggregated bandwidths per fiber for CPO. However, today’s coherent optical transceivers are not yet suitable for CPO applications in AI datacenters. In this proposal, we are introducing Coherent CPO (C2PO) to enable compact and low-power QAM modulation using MRMs.<br/><br/>Unlike today’s datacenter connectivity, future of interconnects will rely on massively parallelized multi-channel energy/area efficient coherent optical links that should be co-packaged with processor and accelerators. Key technologies such as generative AI, autonomous vehicles, AR/VR and 6G all require such a critical backbone technology paradigm shift. Our proposed work enhances key metrics by 10x-100x compared with today’s commercial and R&Ds solutions. Proposed method can be extended in future to higher QAM modulations such as QAM-64 to support data-rates of +1Tb/s per wavelength in each fiber. Education, workforce development, and outreach activities within this project focus on the semiconductor industry's future needs. These activities encompass: Developing course materials for the co-design of RF/High-speed circuits with emerging devices and creating analog layout and design automation (in Python) for high-school internship/outreach programs. PI will leverage various mechanisms to achieve broader impacts in diversity, education, and outreach through this project.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/30/2024
|
07/30/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430776
|
{'FirstName': 'Sajjad', 'LastName': 'Moazeni', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sajjad Moazeni', 'EmailAddress': '[email protected]', 'NSF_ID': '000807598', 'StartDate': '07/30/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'ZipCode': '981951016', 'PhoneNumber': '2065434043', 'StreetAddress': '4333 BROOKLYN AVE NE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Washington', 'StateCode': 'WA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'WA07', 'ORG_UEI_NUM': 'HD1WMN6945W6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WASHINGTON', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'StateCode': 'WA', 'ZipCode': '981951016', 'StreetAddress': '4333 BROOKLYN AVE NE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Washington', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'WA07'}
|
{'Code': '756400', 'Text': 'CCSS-Comms Circuits & Sens Sys'}
|
2024~422653
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430776.xml'}
|
NLI: Design and Development: RUI: Prototyping a systems thinking framework to foster environmental and sociotechnical thinking across an interdisciplinary engineering curriculum
|
NSF
|
09/01/2024
|
08/31/2027
| 349,410 | 349,410 |
{'Value': 'Standard Grant'}
|
{'Code': '07050000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'EEC', 'LongName': 'Div Of Engineering Education and Centers'}}
|
{'SignBlockName': 'Matthew A. Verleger', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922961'}
|
The future engineering workforce demands professionals who, in addition to their technical skills, can evaluate and address the environmental, social, and ethical factors impacting their engineering decisions. In parallel, engineering faculty need pathways to meet emerging workforce needs in both their individual courses and across the engineering curriculum. This work will address these needs by designing, developing, implementing, and assessing a Systems Thinking Framework that undergraduate engineers can apply to coursework, projects, and professional practice. Systems Thinking considers a concept not as a discrete idea but as housed within a broader system, with dynamic and interconnected relationships between system components. Systems Thinking is inherently a sociotechnical approach to problem solving and can promote examining environmental, social, and ethical relationships. The Systems Thinking Framework will be deployed in 5-7 activities across courses in an interdisciplinary engineering curriculum and in an industry-partnered capstone design project. By consistently practicing evaluating the environmental and sociotechnical aspects of engineering design, students will be equipped to contribute this skill upon entering the workforce. To incorporate the Systems Thinking Framework, this project will deploy and evaluate a prototyping process for faculty enacting large-scale curricular change. This prototyping-based change process can further be applied to additional emerging workforce needs. This work is aligned with the NSF-Lemelson Initiative and Research in the Formation of Engineers program goals of effectively integrating environmental and social sustainability into engineering education and enhancing our understanding of curricular change.<br/><br/>Implementation and assessment using student-produced deliverables, surveys, and interviews will answer research questions focused on (i) how students use Systems Thinking to evaluate environmental, social, and ethical implications, (ii) student growth over multiple Systems Thinking experiences, and (iii) comparisons between case-study and open-ended contexts. Expected measurable outcomes include that students will assess the environmental, social, and ethical implications of an engineering technology by defining and evaluating the system, and that students will use Systems Thinking to make design decisions that consider environmental, social, and ethical factors in addition to technical optimality. In parallel, this work will examine how a distributed, coordinated prototyping process can address faculty barriers and drivers towards addressing sustainability and social impacts in their courses. Assessment of the prototyping process through surveys and interviews will contribute to new understanding of faculty needs and effective strategies for large-scale curricular change. The expected measurable outcome for this work is that faculty will demonstrate increased self-efficacy toward instructing on sustainability and sociotechnical impacts. To support applicability and propagation, the Framework and modular course activities (Modules) will be co-created and implemented with faculty partners across institutions through prototyping Community of Practice groups. Graduate students and postdocs from around Southern California will also gain experience teaching Systems Thinking and using prototypes to explore new teaching practices through a summer teaching workshop. All Modules will be made publicly available with a Creative Commons license, including a “Module Skeleton” that can be adapted to new topics.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/15/2024
|
08/15/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430790
|
[{'FirstName': 'Sophia', 'LastName': 'Bahena', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sophia L Bahena', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A00HS', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Whitney', 'LastName': 'Fowler', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Whitney C Fowler', 'EmailAddress': '[email protected]', 'NSF_ID': '000979593', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Leah', 'LastName': 'Mendelson', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Leah Mendelson', 'EmailAddress': '[email protected]', 'NSF_ID': '000764340', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Harvey Mudd College', 'CityName': 'CLAREMONT', 'ZipCode': '917115901', 'PhoneNumber': '9096218121', 'StreetAddress': '301 PLATT BLVD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '28', 'CONGRESS_DISTRICT_ORG': 'CA28', 'ORG_UEI_NUM': 'C76JKA5JY2B3', 'ORG_LGL_BUS_NAME': 'HARVEY MUDD COLLEGE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Harvey Mudd College', 'CityName': 'CLAREMONT', 'StateCode': 'CA', 'ZipCode': '917115901', 'StreetAddress': '301 PLATT BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '28', 'CONGRESS_DISTRICT_PERF': 'CA28'}
|
{'Code': '134000', 'Text': 'EngEd-Engineering Education'}
|
2024~349410
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430790.xml'}
|
EAGER: Investigating a novel role of a micronutrient copper in auxin metabolism and signaling in reproduction in A. thaliana
|
NSF
|
08/01/2024
|
07/31/2026
| 299,974 | 299,974 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Cristiana Argueso', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032925090'}
|
Global food security and the demand for high-yielding grain crops are among the most urgent and ambitious drivers of modern plant sciences due to the current trend of population growth and decreasing arable land resources. The total grain yield is directly linked to crop and soil fertility. In this regard, the limited availability of the micronutrient copper in the soil causes copper deficiency in crop plants. This condition leads to plant infertility and, consequently, low yields. However, the physiological, molecular, and genetic mechanisms underlying this trait are unknown. Besides copper nutritional demands, plant reproduction is regulated by plant hormones. Among them, the hormone auxin has a recognized role in reproductive organ development and patterning. The existence of the relationship between auxin-mediated developmental programs and plant mineral demands has not yet been considered. This project will use multifaceted functional genetics and genomic tools to explore a newly discovered untraditional link between copper function in reproduction and auxin in a model plant, Arabidopsis thaliana. The discoveries made through this award will guide future studies on the interplay between micronutrients and hormone signaling for ensuring normal plant developmental programs. In a broader context, this project is relevant to the future of food security, as it has the potential to contribute to molecular breeding efforts directed at improving crop grain yield on marginal soils. This project will provide unique training opportunities. Through a partnership with the University of Texas at El Paso (UTEP), students at Cornell and UTEP will get hands-on experience in using cutting-edge synchrotron X-ray techniques to address complex biological questions. <br/><br/>Copper is a redox-active micronutrient with a recognized role in plant reproduction and seed yield. Despite this knowledge, the specific function of copper in reproduction, the sites of its action, and the genes controlling its delivery to reproductive organs still needed to be fully understood. The phytohormone auxin regulates every aspect of plant development and is a recognized morphogen that controls reproductive organ development and patterning. Previous work has shown that copper localizes to anthers, pistils, and pollen grains in Arabidopsis thaliana; copper delivery to these reproductive structures requires two transcription factors, CITF1 and SPL7. Failure to deliver copper to these reproductive structures in wild-type grown under acute copper deficiency or in a double mutant lacking CITF1 and SPL7 leads to female and male infertility. Notably, some fertility and shoot architecture defects of copper-deficient and citf1 spl7 mutant plants resembled those observed in auxin synthesis, transport, or signaling mutants. This finding was intriguing, considering that the existence of the relationship between auxin-mediated developmental programs and plant mineral demands has yet to be considered. The proposed studies will uncover whether copper and the CITF1-SPL7-regulated copper homeostatic pathway influence reproduction via acting on auxin metabolism and/or signaling, thereby presenting a radically different perspective on the mechanism of copper action in plant development.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/22/2024
|
07/22/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430791
|
{'FirstName': 'Olena', 'LastName': 'Vatamaniuk', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Olena K Vatamaniuk', 'EmailAddress': '[email protected]', 'NSF_ID': '000205179', 'StartDate': '07/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Cornell University', 'CityName': 'ITHACA', 'ZipCode': '148502820', 'PhoneNumber': '6072555014', 'StreetAddress': '341 PINE TREE RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_ORG': 'NY19', 'ORG_UEI_NUM': 'G56PUALJ3KT5', 'ORG_LGL_BUS_NAME': 'CORNELL UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Cornell University', 'CityName': 'ITHACA', 'StateCode': 'NY', 'ZipCode': '148502820', 'StreetAddress': '341 PINE TREE RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_PERF': 'NY19'}
|
{'Code': '765800', 'Text': 'Physiol Mechs & Biomechanics'}
|
2024~299974
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430791.xml'}
|
ExLENT Beginnings: Preparing Autistic Students for the AI Workforce
|
NSF
|
12/15/2023
|
09/30/2025
| 220,000 | 220,000 |
{'Value': 'Cooperative Agreement'}
|
{'Code': '15020000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'ITE', 'LongName': 'Innovation and Technology Ecosystems'}}
|
{'SignBlockName': 'Leroy Jones II', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924684'}
|
The project aims to serve the national interest by addressing the shortage of talent in the emerging technology of artificial intelligence (AI) through reaching out to untapped populations, such as autistic STEM community college students. Autistic people often demonstrate a strong affinity for STEM; however, they suffer from an 80% unemployment rate due to social stigma and discrimination. Carnegie-Mellon University and Pennsylvania State University at University Park has assembled a team of experts to develop innovative pedagogical materials and scalable tools to teach AI technical skills through a "learning-by-doing" experience, teach crucial team collaboration and communication skills through AI-focused project-based learning, and facilitate autistic community college students to obtain AI-focused summer internships and increase their access to AI careers.<br/><br/>The program will use a strengths-based approach to provide strategies and supports that allow individuals with autism to engage confidently, competently, and with a positive sense of self when navigating the complex and challenging social environment of the workplace. The project’s pedagogical innovations include the human factors and user interface design to support AI subject-matter experts, mentors, and teachers learning to teach autistic students. Special education experts in autism who specialize in teaching communication, social, and teaming skills will support project mentors in their day-to-day learning experiences. Online training will be employed to reach more autistic students and also make the online course materials available to community college teachers to offer this course at their own schools. This project will not only address the employment gap by establishing innovative pathways for autistic students to specialize in AI careers, but more importantly, debunk the harmful stereotypes and change the exclusionary norms that impact their employment. This project aligns with the NSF ExLENT Program, funded by the NSF TIP and EDU Directorates, as it seeks to support experiential learning opportunities for individuals from diverse professional and educational backgrounds to increase their interest in, and their access to, career pathways in emerging technology fields.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/19/2024
|
08/19/2024
|
None
|
CoopAgrmnt
|
47.076, 47.084
|
1
|
4900
|
4900
|
2430805
|
{'FirstName': 'Somayeh', 'LastName': 'Asadi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Somayeh Asadi', 'EmailAddress': '[email protected]', 'NSF_ID': '000627468', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Virginia Main Campus', 'CityName': 'CHARLOTTESVILLE', 'ZipCode': '229034833', 'PhoneNumber': '4349244270', 'StreetAddress': '1001 EMMET ST N', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'VA05', 'ORG_UEI_NUM': 'JJG6HU8PA4S5', 'ORG_LGL_BUS_NAME': 'RECTOR & VISITORS OF THE UNIVERSITY OF VIRGINIA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Virginia Main Campus', 'CityName': 'CHARLOTTESVILLE', 'StateCode': 'VA', 'ZipCode': '229034833', 'StreetAddress': '1001 EMMET ST N', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'VA05'}
|
[{'Code': '199800', 'Text': 'IUSE'}, {'Code': '227Y00', 'Text': 'ExLENT'}]
|
2023~220000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430805.xml'}
|
CIVIC-PG Track B:Data-Driven Analytics for Scaling Up Community Carshare:Advancing Efficiency, Access, Sustainability, and Equity (EASE).
|
NSF
|
10/01/2024
|
03/31/2025
| 74,999 | 74,999 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'David Corman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928754'}
|
The proposed research-centered pilot will support the deployment of data-driven analytics to improve the efficiency, access, sustainability, and equity of the largest community carshare service in the nation and the development of fundamental knowledge about the science and engineering of community carshare. In 2022, the cities of Saint Paul and Minneapolis, Minnesota launched the EV Spot Network in collaboration with HOURCAR, the largest nonprofit carshare provider in the US. The EV Spot Network provides publicly owned electric vehicle (EV) carshare and chargers. The vehicles and chargers are owned by the cities, while HOURCAR operates the service. The system was designed from inception to serve those with the greatest transportation need, with at least half of serviced neighborhoods designated as disadvantaged. The service is planned to grow significantly over the next three years with up to 200 additional EVs to be added in 2025 (and potentially more in subsequent years). Planned growth will allow for expanding the service region, extending the reach of public transit and making cars more available. If successful, the pilot can serve as a template for how community carshare can be scaled up in a cost-effective way while increasing access, reducing environmental footprint, and improving equity.<br/><br/>This scale-up poses challenges that have not been adequately addressed previously in the academic literature or practice and thus provides a unique opportunity to conduct a research-oriented pilot project. The proposed research-centered pilot will deploy data-driven analytics, developed by the research team, to support HOURCAR in making decisions as it seeks to densify of its service, expand its service region, and extend the reach of public transit. Specifically, we envision working with HOURCAR and its stakeholders, to develop and deploy AI based decision support tools for demand estimation, design of the system network, pricing and incentive design, and overall system management and planning. The research will also test the effectiveness of various behavioral modification interventions and incentives that can promote the use of carsharing and enhance the body of social science research on this topic. The approach developed here will demonstrate how community carshare can be scaled up in a cost-effective way while increasing access, reducing environmental footprint, and improving equity. It can also serve as a blueprint for how cities, transit authorities, and community-based organizations can partner to bridge the gap between essential resources and services and community needs.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430807
|
[{'FirstName': 'Yafeng', 'LastName': 'Yin', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yafeng Yin', 'EmailAddress': '[email protected]', 'NSF_ID': '000489707', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Elisabeth', 'LastName': 'Gerber', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Elisabeth R Gerber', 'EmailAddress': '[email protected]', 'NSF_ID': '000332391', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Saif', 'LastName': 'Benjaafar', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Saif Benjaafar', 'EmailAddress': '[email protected]', 'NSF_ID': '000368342', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Paul', 'LastName': 'Schroeder', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Paul Schroeder', 'EmailAddress': '[email protected]', 'NSF_ID': '000833928', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Martin', 'LastName': 'Zubeldia Suarez', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Martin Zubeldia Suarez', 'EmailAddress': '[email protected]', 'NSF_ID': '000987137', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'ZipCode': '481091079', 'PhoneNumber': '7347636438', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'MI06', 'ORG_UEI_NUM': 'GNJ7BBP73WE9', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MICHIGAN', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'StateCode': 'MI', 'ZipCode': '481091274', 'StreetAddress': '3003 S State St', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'MI06'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~74999
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430807.xml'}
|
Nuclear probes of conductivity in Na-ion battery materials
|
NSF
|
08/15/2024
|
07/31/2028
| 548,497 | 548,497 |
{'Value': 'Standard Grant'}
|
{'Code': '03070000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMR', 'LongName': 'Division Of Materials Research'}}
|
{'SignBlockName': 'Nazanin Bassiri-Gharb', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922430'}
|
Non-technical Description<br/>This project explores conductivity in low-cost sodium-based materials for use in rechargeable batteries. Understanding how ions move in a battery is crucial for improving battery performance, including energy density, operating potential, and charge/discharge rates, but our understanding of the relationship between electrical conductivity, ionic conductivity, and diffusion in sodium-ion cathode materials is incomplete. This project, supported by the Ceramics Program in the Division of Materials Research at NSF, will investigate conductivity with experimental probes of the nuclei of atoms in combination with traditional tools to study battery materials. Mossbauer spectroscopy will be used to investigate the interactions between atomic nuclei and its surrounding electrons. Quasielastic neutron scattering will be used to study the dynamics of atoms, providing information about the displacements of atoms on the length scale of Angstroms to nanometers, and time scale of picoseconds to tens of nanoseconds. Together, these techniques will provide new insights that enhance our understanding of conductivity in sodium-ion batteries and promote the development of safer, higher capacity, and more sustainable battery technologies. Sodium-ion batteries are being investigated because of their potential to reduce reliance on lithium and other scarce, high-cost metals. This research addresses the global need for better energy storage solutions, and provides research training opportunities and career mentorship for undergraduate students. It also supports the establishment of a regional center for collaboration on operando and in situ Mossbauer spectroscopy studies.<br/><br/>Technical Summary<br/>The primary goal of this research is to study conductivity in sodium-ion battery cathodes using nuclear probes of Mossbauer spectroscopy and quasielastic neutron scattering to address the roles of electrical conductivity, ionic conductivity, and diffusion in cathodes. Mossbauer spectroscopy is a lab-based technique that probes the hyperfine interactions between the nucleus and the surrounding electrons. Ex situ temperature-dependent Mossbauer will be used to determine activation energies for polaron mobility. In situ measurements of Mossbauer spectra during electrochemical cycling will provide information about phase, oxidation state, and coordination environment during active cycling. Quasielastic neutron scattering (QENS) is a probe of the dynamical relaxation process in a material. Temperature-dependent QENS measurements will be used to study sodium diffusion, revealing temporal and microscopic spatial information about diffusing ions that cannot be gained with other experimental techniques. These complementary nuclear techniques, alongside other commonly used tools for investigating battery materials, will be used to examine three hypotheses about the location and transport of active ions in battery cathode materials. The new knowledge about conductivity in cathodes will advance fundamental understanding of battery cathodes and promote the development of new materials. This research project also trains undergraduate students in energy storage research and creates a pathway for their continuation on to advanced degree programs and careers.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/02/2024
|
08/02/2024
|
None
|
Grant
|
47.049
|
1
|
4900
|
4900
|
2430817
|
{'FirstName': 'Hillary', 'LastName': 'Smith', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hillary Smith', 'EmailAddress': '[email protected]', 'NSF_ID': '000858341', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Swarthmore College', 'CityName': 'SWARTHMORE', 'ZipCode': '190811390', 'PhoneNumber': '6103288000', 'StreetAddress': '500 COLLEGE AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'PA05', 'ORG_UEI_NUM': 'KPALJZQMJAX6', 'ORG_LGL_BUS_NAME': 'SWARTHMORE COLLEGE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Swarthmore College', 'CityName': 'SWARTHMORE', 'StateCode': 'PA', 'ZipCode': '190811390', 'StreetAddress': '500 COLLEGE AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'PA05'}
|
{'Code': '177400', 'Text': 'CERAMICS'}
|
2024~548497
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430817.xml'}
|
Does synergy among litter, organic horizons, and roots bolster nutrient retention and production?
|
NSF
|
05/01/2024
|
10/31/2024
| 74,660 | 10,012 |
{'Value': 'Standard Grant'}
|
{'Code': '06030000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'EAR', 'LongName': 'Division Of Earth Sciences'}}
|
{'SignBlockName': 'Alberto Perez-Huerta', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032920000'}
|
Temperate forests are under increasing environmental stresses from changes in land management, atmospheric pollution, and a changing climate. These environmental changes have important effects on how inorganic nutrients (Magnesium, Phosphorus, Potassium, Calcium) are stored and cycled in the soils of temperate forests. Inorganic nutrients are essential for plant growth and are sourced to soils from mineral weathering, deposition from the atmosphere, and leaf litter from plants. While roots are known for their role in extracting inorganic nutrients for plants, they can contribute organic matter to help store inorganic nutrients in soils. This research project explores how leaf litter and surface roots promote inorganic nutrient storage in soils and the extent of their codependence. To understand climatic controls on leaf litter and roots for inorganic nutrient cycling, the researchers will leverage a network of research sites spanning from the warm temperate forests of Virginia to the cold temperate forests of northern New England. The findings will be used to inform the U.S. Forest Service and several state Forestry and Natural Resources Departments of the current and future inorganic nutrient cycling in their forests. Furthermore, the research site in Massachusetts will serve as an instructional tool for university and community college courses. <br/><br/>The primary objective of the project is to quantify the codependence of leaf litter and roots on Mg, P, K, and Ca stabilization in temperate forest soil. Leaf litter and roots may act synergistically to stabilize inorganic nutrients in the mineral soil through generating organic matter and aggregation. To avoid the common issue of heterogeneity of soil materials and duration of development, the project will leverage soil columns buried three years ago, containing a quartz-feldspar-kaolinite mixture to examine the effect of leaf litter and tree roots on inorganic nutrients in mineral soil. Researchers will quantify the rate of inorganic nutrient stabilization in bulk soils and use microprobe analyses to examine rhizosphere and microaggregation. Moreover, the project will utilize existing litterfall and atmospheric deposition monitoring to estimate nutrient cycling budgets. When examined across the climate gradient, the findings can be used to predict future shifts in nutrient cycling from shifts in leaf litter-root codependence with changes in climate.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
05/17/2024
|
05/17/2024
|
None
|
Grant
|
47.050
|
1
|
4900
|
4900
|
2430820
|
{'FirstName': 'Justin', 'LastName': 'Richardson', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Justin B Richardson', 'EmailAddress': '[email protected]', 'NSF_ID': '000717395', 'StartDate': '05/17/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Virginia Main Campus', 'CityName': 'CHARLOTTESVILLE', 'ZipCode': '229034833', 'PhoneNumber': '4349244270', 'StreetAddress': '1001 EMMET ST N', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'VA05', 'ORG_UEI_NUM': 'JJG6HU8PA4S5', 'ORG_LGL_BUS_NAME': 'RECTOR & VISITORS OF THE UNIVERSITY OF VIRGINIA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Virginia Main Campus', 'CityName': 'CHARLOTTESVILLE', 'StateCode': 'VA', 'ZipCode': '229034833', 'StreetAddress': '1001 EMMET ST N', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'VA05'}
|
{'Code': '722200', 'Text': 'XC-Crosscutting Activities Pro'}
|
2021~10012
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430820.xml'}
|
Conference: Equivariant Homotopy Theory in Context Workshops
|
NSF
|
01/01/2025
|
12/31/2025
| 30,000 | 30,000 |
{'Value': 'Standard Grant'}
|
{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
|
{'SignBlockName': 'Swatee Naik', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924876'}
|
This award provides travel support for early career US-based mathematicians to attend four workshops during the semester program “Equivariant Homotopy Theory in Context” at the Isaac Newton Institute for Mathematical Sciences in Cambridge, UK in the first half of 2025.The workshop names and dates are:<br/>1. Introductory workshop for Equivariant Homotopy Theory in Context, January 13-17, 2025<br/>2. Operads and calculus, April 7-11, 2025<br/>3. New horizons for equivariance in homotopy theory, May 12-16, 2025<br/>4. Beyond the telescope conjecture, June 16-20, 2025<br/>Priority for funding will be given to those who do not have funds from other sources . The direct impact of NSF funding will be the training and career development of up to 30 researchers, by means of the opportunity to participate in a major program in Europe and at the Newton Institute, in particular, which is a major international nexus in mathematics. A secondary impact is to further develop collaboration between emerging research groups in algebraic topology and derived algebraic geometry in the US and Europe, in particular the United Kingdom. Holding this program as well as the workshops at the Newton Institute for Mathematical Sciences makes particular sense, because this is an international field, with leaders in many countries.<br/><br/>The last decade has seen an explosion of exciting results in homotopy theory and related areas of algebraic geometry, algebra, and the algebraic topology of manifolds. Crucial here are new equivariant techniques, the study of symmetries and group actions in algebraic topology. Historically, advances in differential topology depended on the solution of basic homotopy theoretic questions and, in the same way, the advent of equivariant homotopy theory was guided by the study of manifolds with group actions. It quickly became much more than that and the interplay between equivariant homotopy theory and its applications in algebraic K-theory, chromatic homotopy theory, functor calculus, and other fields drove a self-reinforcing narrative that is only expanding now. This semester-long program and workshops are building on this momentum and creating an environment for further exchange of ideas. Workshop websites are: <br/>https://www.newton.ac.uk/event/ehtw01/<br/>https://www.newton.ac.uk/event/ehtw02/<br/>https://www.newton.ac.uk/event/ehtw03/<br/>https://www.newton.ac.uk/event/ehtw04/<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/06/2024
|
08/06/2024
|
None
|
Grant
|
47.049
|
1
|
4900
|
4900
|
2430825
|
[{'FirstName': 'Paul', 'LastName': 'Goerss', 'PI_MID_INIT': 'G', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Paul G Goerss', 'EmailAddress': '[email protected]', 'NSF_ID': '000280871', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Vesna', 'LastName': 'Stojanoska', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Vesna Stojanoska', 'EmailAddress': '[email protected]', 'NSF_ID': '000631405', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Irina', 'LastName': 'Bobkova', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Irina Bobkova', 'EmailAddress': '[email protected]', 'NSF_ID': '000708511', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Texas A&M University', 'CityName': 'COLLEGE STATION', 'ZipCode': '778454375', 'PhoneNumber': '9798626777', 'StreetAddress': '400 HARVEY MITCHELL PKY S STE 30', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'TX10', 'ORG_UEI_NUM': 'JF6XLNB4CDJ5', 'ORG_LGL_BUS_NAME': 'TEXAS A & M UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Isaac Newton Institute', 'CityName': 'Cambridge', 'StateCode': None, 'ZipCode': 'CB3 0EH', 'StreetAddress': '20 Clarkson Road', 'CountryCode': 'UK', 'CountryName': 'United Kingdom', 'StateName': 'RI REQUIRED', 'CountryFlag': '0', 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
|
{'Code': '126700', 'Text': 'TOPOLOGY'}
|
2024~30000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430825.xml'}
|
ENG-ADVWIRE:CCSS: RF Interference Mitigation in High-Density Heterogeneous Semiconductor Device Packaging Through Digital Twin Emulations
|
NSF
|
11/01/2024
|
10/31/2026
| 400,000 | 400,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Jenshan Lin', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927360'}
|
Future electronics manufacturing will not only encompass devices like chips and chiplets but also integrate passive components, sensors, and Radio Frequency (RF) front ends with power amplifiers into high-density heterogeneous packages. Currently, package components are tested individually and reassembled on high-density interposer substrates. However, future trends indicate that the interconnect pitch between devices will scale down to less than a micron. This shift towards high-density integration necessitates more sophisticated methods to mitigate electromagnetic interference (EMI) and ensure electromagnetic compatibility (EMC) within the overall package. With this in mind, this research focuses on thin film magnetodielectric materials and electronic package topologies, coupled with Multiphysics digital twin models, aimed at suppressing: 1) jittering and degradation of bit error rates, 2) switching noise in digital integrated circuits due to emissions or crosstalk, 3) close proximity coupling and radiation due to high-speed digital or analog interconnects, and 4) transmission line crosstalk due to conduction or ground bounces of electromagnetic fields. The primary goal of this project is to develop new techniques for predicting and suppressing signal interference in future high-density electronic packages. Concurrently, the project will develop a comprehensive multiphysics toolset to integrate circuit extraction methods and materials for EMI suppression with popular chip and electronic/RF circuit toolsets seamlessly. This research is expected to impact the rapidly growing U.S. semiconductor industry and enable the packaging of reliable, vertically integrated electronics. Additionally, it will substantially enhance the training of a diverse group of students by leveraging Florida International University's unique position as the only Majority-Minority Carnegie R1 Research University in the continental U.S. This research will further advance educational efforts to broaden participation of women and other underrepresented groups in STEM through curriculum development and REU programs.<br/><br/>The aim of this research is to pioneer disruptive EMI/EMC mitigation techniques in high-density heterogeneous semiconductor device packages through digital twin emulations. The goal is to advance knowledge and enable optimal embedded packaging with heterogeneous active and passive components to ensure future electronic package reliability and performance. To address these challenges, the project will investigate: a) new EMI/EMC ferromagnetic composite materials, b) novel packaging topologies, and c) advanced computational and circuits extraction methods. A number of innovations are expected: 1) multilayered films formed of cobalt nickel-iron alloy (CoNiFe) and copper (Cu) layers, but still only 5 micrometers thick, to achieve maximum shielding with minimal film thickness. As much as 30 dB more shielding can be attained using these composite films; 2) New shielding topologies for reliable interference suppression using prefabricated forms to enable rapid electronic package formations. These are aimed at suppressing high-power device interference and high-speed circuit radiation at the chip interconnects (as much as 40 dB or more); 3) New class of multiphysics toolsets that cut across electromagnetic, thermomechanical and thermal designs to provide system performance and reliability. Such multiphysics models are of critical importance as interactions among various physics domains imply design trade-offs needing quantification; 4) AI multiphysics models that combine model-agnostic meta-learning and physics-informed learning approaches using measured data as well as analytical and semi-analytical models for accurate and robust modeling; 5) Novel S-parameter extraction methods that uniquely account for coupling and external fields using new port excitations within the circuit network of the multiphysics model.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/24/2024
|
07/24/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430828
|
[{'FirstName': 'John', 'LastName': 'Volakis', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'John L Volakis', 'EmailAddress': '[email protected]', 'NSF_ID': '000272422', 'StartDate': '07/24/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Markondeya Raj', 'LastName': 'Pulugurtha', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Markondeya Raj Pulugurtha', 'EmailAddress': '[email protected]', 'NSF_ID': '000793199', 'StartDate': '07/24/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Konstantinos', 'LastName': 'Zekios', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Konstantinos Zekios', 'EmailAddress': '[email protected]', 'NSF_ID': '000867152', 'StartDate': '07/24/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Florida International University', 'CityName': 'MIAMI', 'ZipCode': '331992516', 'PhoneNumber': '3053482494', 'StreetAddress': '11200 SW 8TH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '26', 'CONGRESS_DISTRICT_ORG': 'FL26', 'ORG_UEI_NUM': 'Q3KCVK5S9CP1', 'ORG_LGL_BUS_NAME': 'FLORIDA INTERNATIONAL UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'Q3KCVK5S9CP1'}
|
{'Name': 'Florida International University', 'CityName': 'MIAMI', 'StateCode': 'FL', 'ZipCode': '331992516', 'StreetAddress': '11200 SW 8TH ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '26', 'CONGRESS_DISTRICT_PERF': 'FL26'}
|
{'Code': '756400', 'Text': 'CCSS-Comms Circuits & Sens Sys'}
|
2024~400000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430828.xml'}
|
Conference: 8th International Plant Phenotyping Symposium 2024
|
NSF
|
09/01/2024
|
02/28/2025
| 17,160 | 17,160 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Shin-Han Shiu', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032920000'}
|
The 8th International Plant Phenotyping Symposium (IPPS) will be held at the University of Nebraska-Lincoln on October 7-11, 2024. The International Plant Phenotyping Network (IPPN), who organizes this event, is the premier international scientific organization in plant phenotyping. Plant phenotyping, or phenomics, is a scientific discipline that is essential to capturing information about plant biology, gene-by-environment interactions, and ecological/environmental stewardship. Capturing this information is essential to providing food and feed security to a growing global population while caring for our planet. The IPPS is the leading international platform for the presentation of the most exciting research and application in plant phenotyping across the globe and the IPPS8 is the first time that this event will be held in the US. The broader impacts of this proposal lie in the future research advances that will come from the resulting interactions and networking among plant phenotyping scientists. Such advances will yield improved strategies for increasing domestic plant production while improving plant ecosystem health for the benefits of society. <br/><br/>While the IPPS is the leading international platform for research and application in plant phenotyping, the NAPPN Strategic Meeting will assemble stakeholders in plant phenotyping to develop a strategic plan for the domestic plant phenotyping community. Phenomics is an interdisciplinary science where plant systems biology, quantitative genetics, metabolomics, and agronomy intersect with intensive computational science and engineering, and technologies for remote sensing, imaging, and robotics. As such, effective phenotyping requires knowledge sharing and communication across disciplines and economic sectors (academia, non-profit, government, industry). Phenotyping science occurs across biological scales, from molecular to cellular to organismal to ecological. The IPPS8 will be advertised through established research coordination networks and organizations (MANNRS, HBCUs, Tribal Colleges). Travel awardees will have an opportunity to share their own research through oral or poster presentations and “lightning talks”. These attendees will be paired with `conference mentors` to enhance their in-person experience. Accessibility to IPPS8 content will be provided by recording selected talks to be distributed virtually post-conference and in the form of short papers in a special edition of a journal.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
06/17/2024
|
06/17/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2430842
|
[{'FirstName': 'Jennifer', 'LastName': 'Clarke', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jennifer L Clarke', 'EmailAddress': '[email protected]', 'NSF_ID': '000512667', 'StartDate': '06/17/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Seth', 'LastName': 'Murray', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Seth C Murray', 'EmailAddress': '[email protected]', 'NSF_ID': '000522716', 'StartDate': '06/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Anjali', 'LastName': 'Iyer-Pascuzzi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Anjali Iyer-Pascuzzi', 'EmailAddress': '[email protected]', 'NSF_ID': '000639861', 'StartDate': '06/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Alexander', 'LastName': 'Bucksch', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Alexander Bucksch', 'EmailAddress': '[email protected]', 'NSF_ID': '000646639', 'StartDate': '06/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Nebraska-Lincoln', 'CityName': 'LINCOLN', 'ZipCode': '685032427', 'PhoneNumber': '4024723171', 'StreetAddress': '2200 VINE ST # 830861', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Nebraska', 'StateCode': 'NE', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NE01', 'ORG_UEI_NUM': 'HTQ6K6NJFHA6', 'ORG_LGL_BUS_NAME': 'BOARD OF REGENTS OF THE UNIVERSITY OF NEBRASKA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Nebraska-Lincoln', 'CityName': 'LINCOLN', 'StateCode': 'NE', 'ZipCode': '685032427', 'StreetAddress': '2200 VINE ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Nebraska', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NE01'}
|
{'Code': '132900', 'Text': 'Plant Genome Research Project'}
|
2024~17160
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430842.xml'}
|
Doctoral Dissertation Research: Inter Society Social Integration.
|
NSF
|
09/01/2024
|
08/31/2025
| 38,518 | 38,518 |
{'Value': 'Standard Grant'}
|
{'Code': '04040000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'BCS', 'LongName': 'Division Of Behavioral and Cognitive Sci'}}
|
{'SignBlockName': 'John Yellen', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928759'}
|
This doctoral dissertation project examines the mechanisms of sociopolitical formation among ancestrally diverse people in colonial contexts. Anthropologists have long been interested in the outcomes of group formation. Fundamentally, how do people negotiate differences to build new social and political communities? Recent research challenges how scholars delineate ethnic boundaries in the past and their political implications for Indigenous and diasporic communities today. Multidisciplinary scholarship has demonstrated that Indigenous societies frequently built their nations by expanding kin ties, thereby forming adaptable political institutions and societies; this framework contrasts with widely held expectations for race-based ancestry and bordered sovereignty. These dynamics also challenge archaeological studies of community coalescence, which frequently assume political economy is a key driver of social and material change. As such, this study uses archaeological evidence from households to investigate the role and material correlates of small-scale integrative strategies––specifically daily practice, kinship, and local interaction––in sociopolitical formation. The research focuses on Western frameworks of nationhood and citizenship that legally code Indigenous identity and political sovereignty today. <br/><br/>By using multiple analytical methods, this project joins a community of practice framework (meaning people are connected through a shared way of doing) with a formal social network analysis. Social network analysis is a powerful tool for empirically evaluating and visualizing the social relationships that emerge from shared practice. This approach is applied to an investigation of the one Native American “nation” that coalesced from disparate communities in the early eighteenth century. To understand how individuals built a nation over a few decades, this dissertation project combines extant and new data from household contexts at six archaeologically identified towns. Analysis identifies patterns of social learning that underlaid ceramic production and foodways among women. From ceramics, researchers identify manufacture and decorative decisions through macro-, micro-, and chemical attribute techniques. From plant and animal remains, researchers identify species and processing techniques to understand how Y households managed food resources within a broader political-economic context. Household practices are then compared within and across towns through social network analysis to identify discrete communities of practice.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/26/2024
|
07/26/2024
|
None
|
Grant
|
47.075
|
1
|
4900
|
4900
|
2430847
|
[{'FirstName': 'Robin', 'LastName': 'Beck', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robin Beck', 'EmailAddress': '[email protected]', 'NSF_ID': '000610601', 'StartDate': '07/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Hannah', 'LastName': 'Hoover', 'PI_MID_INIT': 'G', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hannah G Hoover', 'EmailAddress': '[email protected]', 'NSF_ID': '000917750', 'StartDate': '07/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'ZipCode': '481091079', 'PhoneNumber': '7347636438', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'MI06', 'ORG_UEI_NUM': 'GNJ7BBP73WE9', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MICHIGAN', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'StateCode': 'MI', 'ZipCode': '481091079', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'MI06'}
|
{'Code': '760600', 'Text': 'Archaeology DDRI'}
|
2024~38518
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430847.xml'}
|
PSID 2025: Continuity and Change in American Economic and Social Life
|
NSF
|
09/01/2024
|
08/31/2029
| 10,999,998 | 5,500,000 |
{'Value': 'Continuing Grant'}
|
{'Code': '04050000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SES', 'LongName': 'Divn Of Social and Economic Sciences'}}
|
{'SignBlockName': 'Nancy Lutz', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927280'}
|
The Panel Study of Income Dynamics (PSID) is a cornerstone of data infrastructure for social science research in the United States. The study has used a series of surveys to gather information on US families since 1968. Children and grandchildren from the original PSID families now participate as well; the result is data that follows families through several generations. The long timespan allows scientific investigation of questions about how people and families grow and change over time. This includes the study of economic outcomes such as employment, income, and wealth, research on how early life experiences affect employment and health in adulthood, research on how U.S. families cope with the needs of aging family members, and work that examines how key economic variables like consumption and employment are affected by broader businesses cycles and unanticipated events. The research team will collect one new wave of data. The new wave will include measurements of the longer run effect of the COVID-19 pandemic on PSID families. This includes measurements of the direct health impacts of the disease, the effects of disruptions to employment and education, and whether family members were helped by government efforts to reduce the burden of the pandemic. The PIs also plan new measurements of participation in short term ‘gig economy’ jobs, will expand valuable administrative data linkages, and will continue their current effort to expand web-based administration of the PSID questionnaire. The project promotes the national interest by maintaining U.S. leadership in science, by making data available to a broad community of researchers interested in understanding American families, and by providing necessary data to evaluate the long-term impacts of past policy decisions at the federal, state, and local levels of government.<br/><br/>The PSID is the world's longest running household panel survey. Through its long-term measures of economic and social wellbeing, the study allows researchers and policy analysts to investigate the dynamism inherent in social and behavioral process. The long panel, genealogical design, and broad content provide scientists a unique and powerful opportunity to study change within the same family over decades. Collecting additional waves of data from the PSID families contributes to scientific understanding of the dynamics of economic and social behavior. The extended time series of data supports new and systematic investigation of a myriad of questions in the full range of scientific disciplines that study how humans grow and change over the life cycle. This includes the study of economic outcomes (for example, the changes that occur across business cycles and changes in response to increased international economic competition), the study of intergenerational transmission of wealth and income, and the study of how income and health in adulthood and old age depend on early-life experiences. Consistent measures over time are important for accurately estimating the dynamics of these behaviors. Gathering data from the same families over many years improves the precision of the measurement as multiple measures are collected within the same families as well as from multiple families over a period of decades. The investigators will carry out numerous innovations and enhancements while maintaining core data collection for comparability. The PSID creates broader impacts in many ways. It is used by an interdisciplinary community and is increasingly important in health research. The data archive is used to inform public policy; at least nine federal agencies use PSID data. The PSID is also an important resource for teaching and learning. The data are free and publicly available. They are widely used by graduate and undergraduate students. The award funds web-based outreach activities that will make the PSID an even more valuable tool for teaching and learning.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/08/2024
|
08/08/2024
|
None
|
Grant
|
47.075
|
1
|
4900
|
4900
|
2430850
|
[{'FirstName': 'Katherine', 'LastName': 'McGonagle', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Katherine McGonagle', 'EmailAddress': '[email protected]', 'NSF_ID': '000110723', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Narayan', 'LastName': 'Sastry', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Narayan Sastry', 'EmailAddress': '[email protected]', 'NSF_ID': '000166324', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Esther', 'LastName': 'Friedman', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Esther M Friedman', 'EmailAddress': '[email protected]', 'NSF_ID': '000878976', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Thomas', 'LastName': 'Crossley', 'PI_MID_INIT': 'F', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Thomas F Crossley', 'EmailAddress': '[email protected]', 'NSF_ID': '000973430', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'ZipCode': '481091079', 'PhoneNumber': '7347636438', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'MI06', 'ORG_UEI_NUM': 'GNJ7BBP73WE9', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MICHIGAN', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'StateCode': 'MI', 'ZipCode': '481091079', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'MI06'}
|
{'Code': '277Y00', 'Text': 'RI Social & Behavioral Science'}
|
2024~5500000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430850.xml'}
|
EAGER: A Stretchable Ion Barrier for Bioelectronic Encapsulation
|
NSF
|
10/01/2024
|
09/30/2025
| 100,000 | 100,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Richard Nash', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032925394'}
|
Stretchable bioelectronic devices are essential for seamless integration with biological tissue, providing substantial benefits for biomedical applications. However, these devices face a fundamental challenge in maintaining their performance over time in the physiological environment. That is, ions from the surrounding environment gradually diffuse into the dielectric encapsulations, causing electrical leakage and degrading insulation over time. This EAGER project aims to develop a non-leaky, stretchable dielectric encapsulation. The research will focus on investigating heterogeneous materials and structures that mimic cell membranes, specifically emulating the bilayer that prevents ion transport. The outcomes of this research could lead to significant advancements in bioelectronic interfaces that are simultaneously stretchable and ion-impermeable, allowing reliable operation under physiological conditions for extended periods (e.g., lifetime). Additionally, this project offers a comprehensive interdisciplinary research and education program for graduate and undergraduate students, covering diverse fields such as interfacial science, mechanics, nanofabrication, materials science, and bioengineering. <br/><br/>The fact that ion permeability and material stretchability are inextricably linked at the molecular level imposes a fundamental limit on soft materials’ ability to inhibit ion diffusion. This EAGER project addresses this fundamental limit by creating a bioinspired stretchable ion barrier that emulates the cell’s phospholipid bilayer so as to realize stretchable yet ion-impermeable dielectrics. Using only existing stretchable materials, the research focuses on engineering them to mimic the lipid bilayer and investigate (1) the underlying science mechanism, (2) the mechanical robustness, and (3) the electrical stability of the stretchable ion barrier through theoretical and experimental studies. This research is expected to provide new ideas for reconciling two mutually exclusive material properties through biomimetic engineering designs. In particular, it helps remove the major roadblock for bioelectronics to accurately record and stimulate biological signals in vivo over extremely long durations.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/10/2024
|
07/10/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430855
|
{'FirstName': 'Tingyi', 'LastName': 'Liu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tingyi Liu', 'EmailAddress': '[email protected]', 'NSF_ID': '000812284', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Massachusetts Amherst', 'CityName': 'AMHERST', 'ZipCode': '010039252', 'PhoneNumber': '4135450698', 'StreetAddress': '101 COMMONWEALTH AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'MA02', 'ORG_UEI_NUM': 'VGJHK59NMPK9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MASSACHUSETTS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Massachusetts Amherst', 'CityName': 'Hadley', 'StateCode': 'MA', 'ZipCode': '010359450', 'StreetAddress': 'c/o Office of Pre-Award Services', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'MA02'}
|
{'Code': '756400', 'Text': 'CCSS-Comms Circuits & Sens Sys'}
|
2024~100000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430855.xml'}
|
CIVIC-PG Track B: Rehab for America: Housing Resilience for Detroit Communities
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'David Corman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928754'}
|
Rehab for America: Housing Resilience for Detroit Communities addresses the nation’s acute housing crisis through the rehabilitation of vacant homes. Potential homebuyers are being priced-out of even the most affordably built new housing. Yet, in many communities, unoccupied, salvageable structures are ready to be converted to viable housing. Through Rehab for America, University of Michigan researchers will work with the Detroit Land Bank Authority (DLBA), Community Development Advocates of Detroit (CDAD), and aspiring home purchasers/rehabbers to make the rehabilitation process more attainable. Using innovative construction methods and materials, toolkits and training, and funding sources, homeowners will be empowered to conduct repairs and/or work more effectively with contractors, tapping the wealth of DLBA structures (currently 6841), contributing solutions that are expeditious, equitable, and resilient. Our vision is to increase homeownership for Detroit residents by making rehab construction affordable and homes more sustainable so they’re cheaper to heat, cool, and maintain in the service of increasing mental and physical well-being, household wealth, and neighborhood property values.<br/><br/>Rehab for America addresses an important component of the nation’s housing affordability crisis by creating resources for and efficiencies in the process of rehabilitating vacant homes in America’s post-industrial cities. It envisions new service design; construction materials, methods, and efficiencies; and recommendations for financing to improve the success of homeowners and nonprofit developers purchasing and rehabilitating DLBA held properties. We aim to lower the barriers to structural rehabilitation through a three-pronged approach: the development of a better communication strategy and servicing by the DLBA, the creation of tactical approaches to aid in construction, and identification of funding models. The team of architects, engineers, and planners will partner with the DLBA to develop more robust forms of communication with buyers and nonprofit developers about rehabilitating properties. Working with the non-profit Community Development Advocates of Detroit (CDAD) we will engage community partners to identify new or underutilized funding sources to offset the cost of home repair. During the pilot project (Stage 2) we will rehab a DLBA property creating models and demonstrations for best practices. The goals to be assessed during the project include: lowered energy costs through life-cycle building performance and long-term maintenance through material and method specification; increased home value; rebuilding of community; better health outcomes; increased trust among stakeholders, and job training. Piloting the project in Detroit, the service design and products will be modeled for applicability to communities across the United States.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/02/2024
|
08/02/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430862
|
[{'FirstName': 'Sharon', 'LastName': 'Haar', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sharon H Haar', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A057L', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Adam', 'LastName': 'Fure', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Adam Fure', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A063V', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ellie', 'LastName': 'Abrons', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ellie Abrons', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A05T9', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'ZipCode': '481091079', 'PhoneNumber': '7347636438', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'MI06', 'ORG_UEI_NUM': 'GNJ7BBP73WE9', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MICHIGAN', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'StateCode': 'MI', 'ZipCode': '481091079', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'MI06'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430862.xml'}
|
ENG-SEMICON: Meshed chemical sensor network for targeted monitoring of environmental VOCs of concern
|
NSF
|
09/01/2024
|
08/31/2027
| 400,000 | 400,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Richard Nash', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032925394'}
|
Across the United States, wildfires are increasing in frequency, size, and duration. They blanket huge regions of the US with fire smoke, exposing millions of Americans across multiple states to dangerous air quality for days or even weeks. Currently, Americans have access to systems like the EPA’s AirNow to check current air pollution levels in their community, known as the AQI (Air Quality Index) score, to see if they should take any precautions before going outside. However, this score only considers certain types of pollution like ozone or particulate matter but does not consider a specific type of pollution: certain chemicals found in fire smoke known as volatile organic compounds (VOCs) that are known to cause cancer. Currently, there is no technology available to monitor our air for this type of VOC pollution. This project will develop devices that can monitor VOC pollution outdoors so that, long term, Americans can have a more complete picture of air quality in their region, and know when to take action to keep themselves safe and healthy. <br/>The team in this award will assemble a network of portable chemical sensors that can continuously monitor outdoor air, targeting specific carcinogenic VOCs such as benzene, toluene, and xylene. Devices can be set outside and will continuously measure VOCs, relaying data to a cloud for data processing to provide quantitative concentrations. Targeted VOC measurements will be accomplished using gas chromatography coupled with a differential mobility spectrometer chemical detector. First, the team will test different sensor packaging that ensures devices can survive harsh outdoor conditions long term such as heat, rain, or wind, while making accurate measurements. Also, the team will develop wireless communication capabilities for the chemical sensor network, which will relay data over long ranges using the LoRa radio communication technique. The team will test a prototype sensor network under controlled conditions using controlled releases of VOCs inside an airplane hangar, and outside using controlled burns. They will also test the sensor network in an actual wildfire event, to track the real time distribution of cancer causing VOCs within the afflicted community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/12/2024
|
08/12/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430865
|
{'FirstName': 'Cristina', 'LastName': 'Davis', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Cristina E Davis', 'EmailAddress': '[email protected]', 'NSF_ID': '000242622', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-Davis', 'CityName': 'DAVIS', 'ZipCode': '956186153', 'PhoneNumber': '5307547700', 'StreetAddress': '1850 RESEARCH PARK DR STE 300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'CA04', 'ORG_UEI_NUM': 'TX2DAGQPENZ5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, DAVIS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-Davis', 'CityName': 'DAVIS', 'StateCode': 'CA', 'ZipCode': '956186153', 'StreetAddress': '1850 RESEARCH PARK DR STE 300', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'CA04'}
|
{'Code': '756400', 'Text': 'CCSS-Comms Circuits & Sens Sys'}
|
2024~400000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430865.xml'}
|
Conference: Texas Geometry and Topology Conference
|
NSF
|
11/01/2024
|
10/31/2028
| 97,614 | 64,918 |
{'Value': 'Continuing Grant'}
|
{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
|
{'SignBlockName': 'Christopher Stark', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924869'}
|
The Fall 2024 meeting of the Texas Geometry and Topology Conference will be at Texas A&M on November 8-10, 2024. To date the Texas Geometry and Topology Conference has been held spring and fall since its founding in 1989, a total of 67 times. The conference has become an extremely successful semiannual event in the Southwest. The next series of conferences will have seven primary host universities: Rice University, Texas A&M University, The University of Texas at Dallas, University of Houston, Texas Tech University, and (jointly) Texas Christian University and The University of Texas at Arlington.<br/><br/>By design, the Texas Geometry and Topology Conference has two high-impact foci. First, the conference makes it possible for the community of geometers and topologists from Texas and surrounding states (a huge geographic region) to meet and share mathematics on a regular basis. In so doing, the conference is committed to bring researchers of national and international stature to discuss their research as well as offering a venue for regional scholars and early career researchers. This stimulates individual research and generates productive cooperative efforts between schools. Second, the conference is committed to the strengthening and enrichment of the mathematics personnel base. In order that there be no barrier to participation, the conference is widely advertised, participation is open, and there are no registration fees. Graduate students, junior faculty, women, minorities, and persons with disabilities are especially encouraged to participate and to apply for support. Furthermore the conference is partnering with two historically black universities (Fayetteville State University and Prairie View A&M University) on a project to foster research opportunities for select junior faculty at these institutions.<br/><br/>The permanent web page for the Texas Geometry and Topology Conference: http://www.math.tamu.edu/~tgtc/archive/.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/27/2024
|
08/27/2024
|
None
|
Grant
|
47.049
|
1
|
4900
|
4900
|
2430866
|
[{'FirstName': 'Igor', 'LastName': 'Zelenko', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Igor Zelenko', 'EmailAddress': '[email protected]', 'NSF_ID': '000516569', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Dean', 'LastName': 'Baskin', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dean R Baskin', 'EmailAddress': '[email protected]', 'NSF_ID': '000538409', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Zhizhang', 'LastName': 'Xie', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zhizhang Xie', 'EmailAddress': '[email protected]', 'NSF_ID': '000601196', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Texas A&M University', 'CityName': 'COLLEGE STATION', 'ZipCode': '778454375', 'PhoneNumber': '9798626777', 'StreetAddress': '400 HARVEY MITCHELL PKY S STE 30', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'TX10', 'ORG_UEI_NUM': 'JF6XLNB4CDJ5', 'ORG_LGL_BUS_NAME': 'TEXAS A & M UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Texas A&M University', 'CityName': 'COLLEGE STATION', 'StateCode': 'TX', 'ZipCode': '778403368', 'StreetAddress': '3368 TAMU', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'TX10'}
|
{'Code': '126700', 'Text': 'TOPOLOGY'}
|
2024~64918
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430866.xml'}
|
I-Corps: Translation potential of skin graft expansion in split-thickness skin graft surgeries
|
NSF
|
07/01/2024
|
06/30/2025
| 50,000 | 50,000 |
{'Value': 'Standard Grant'}
|
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
|
{'SignBlockName': 'Jaime A. Camelio', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922061'}
|
The broader impact of this I-Corps project is the development of a new skin grafting method that enhances healing for chronic wounds like those from burns, skin cancer, and diabetes. This project introduces an advanced technique aimed at maximizing skin area expansion during split-thickness skin graft surgery while minimizing mechanical strain within grafts. The commercial potential of this innovation lies in its ability to reduce the amount of healthy skin needed for grafting procedures, thereby minimizing patient trauma and improving recovery. Additionally, by minimizing strain generated within grafts, this solution reduces the likelihood of cell activation, thereby decreasing the risk of postoperative complications such as secondary skin contracture. Beyond benefiting individual patients, this technology could set new standards in surgical practices, leading to more efficient healthcare delivery and lower long-term healthcare costs. <br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of precise mathematical models and experimental techniques that unravel the complexities of skin graft mechanics. This research has led to the creation of innovative meshing patterns for skin grafts that enhance graft expansion and minimize internal strain, minimizing donor site trauma and improving healing outcomes. These advancements are based on solid mechanobiological principles and represent a significant improvement over traditional skin grafting techniques, which often result in skin waste and even graft failure.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
06/17/2024
|
06/17/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2430891
|
{'FirstName': 'Farid', 'LastName': 'Alisafaei', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Farid Alisafaei', 'EmailAddress': '[email protected]', 'NSF_ID': '000972472', 'StartDate': '06/17/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'New Jersey Institute of Technology', 'CityName': 'NEWARK', 'ZipCode': '071021824', 'PhoneNumber': '9735965275', 'StreetAddress': '323 DR MARTIN LUTHER KING JR BLV', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'NJ10', 'ORG_UEI_NUM': 'SGBMHQ7VXNH5', 'ORG_LGL_BUS_NAME': 'NEW JERSEY INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'New Jersey Institute of Technology', 'CityName': 'NEWARK', 'StateCode': 'NJ', 'ZipCode': '071021824', 'StreetAddress': '323 DR MARTIN LUTHER KING JR BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'NJ10'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430891.xml'}
|
Leveraging Epitaxial Growth to Deconvolute Particle Size and Density Effects in Thermal Catalysis
|
NSF
|
09/01/2024
|
08/31/2027
| 328,132 | 328,132 |
{'Value': 'Standard Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Robert McCabe', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924826'}
|
Management of waste plastics and other polymeric materials has become a critical environmental issue in recent years. Effective mitigation has generated research and development efforts to “up-cycle” waste plastic to more valuable chemicals or embrace “circular” plastics process technology. When combined with more efficient manufacturing processes, the re-use of plastics, in any form, stands to contribute significantly to net-zero carbon emissions. To those goals, the project investigates a novel catalyst design to break down polyolefin-based plastics (e.g., polyethylene or polypropylene) into smaller molecules that can be used as building blocks for either the remanufacture of polymeric materials or production of commodity chemicals. The novel catalyst design improves overall manufacturing efficiency by lowering energy requirements and directing the chemistry towards desired products. Beyond the technical aspects, the project includes educational and outreach initiatives promoting STEM opportunities for K-12 students, and training opportunities for both undergraduate and PhD students.<br/><br/>The project investigates an aspect of supported heterogeneous supported metal catalyst design that is typically not considered or controlled, i.e., the relationship between particle size and particle density. Specifically, this will be accomplished by varying the particle size and site density of rutile-RuO2 supported on rutile-SnxTi1-xO2 where x ranges from 0 to 1 and to study the effects of these parameters on polyolefin hydrogenolysis. The project leverages the lead investigator’s skills in catalysis with polymer characterization and synthesis capabilities at the University of Akron, thus enabling new methods to analyze polymer upcycling kinetics on well-controlled polymer samples. The RuO2 particle size will be controlled by varying the calcination temperature and/or the misfit strain during epitaxial growth of RuO2 on the rutile-oxide support. Site density will be controlled by the metal precursor loading. Polyolefins (POs) are ideal substrates, and PO hydrogenolysis is a well-chosen probe reaction for elucidating the kinetics as related to the effects of particle size vs density, given the large substrate size and potential for oligomers to bridge multiple particles. The study thus carries practical implications for polymer upcycling, benefitting from new “drop-in” catalyst technology potentially applicable to a broad range of catalytic processes.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/15/2024
|
08/15/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430908
|
{'FirstName': 'Linxiao', 'LastName': 'Chen', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Linxiao Chen', 'EmailAddress': '[email protected]', 'NSF_ID': '000988128', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Akron', 'CityName': 'AKRON', 'ZipCode': '443250001', 'PhoneNumber': '3309722760', 'StreetAddress': '302 BUCHTEL COMMON', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'OH13', 'ORG_UEI_NUM': 'DFNLDECWM8J8', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY OF AKRON', 'ORG_PRNT_UEI_NUM': 'DFNLDECWM8J8'}
|
{'Name': 'University of Akron', 'CityName': 'AKRON', 'StateCode': 'OH', 'ZipCode': '443250001', 'StreetAddress': '302 BUCHTEL COMMON', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Ohio', 'CountryFlag': '1', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_PERF': 'OH13'}
|
[{'Code': '140100', 'Text': 'Catalysis'}, {'Code': '164200', 'Text': 'Special Initiatives'}]
|
2024~328132
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430908.xml'}
|
EAGER: PBI: Assessing Societal and Economic Impacts of Place-Based Innovation with Small Area Innovation Rate Estimation
|
NSF
|
09/01/2024
|
08/31/2026
| 299,998 | 299,998 |
{'Value': 'Standard Grant'}
|
{'Code': '15020000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'ITE', 'LongName': 'Innovation and Technology Ecosystems'}}
|
{'SignBlockName': 'Rebecca Shearman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927403'}
|
Place-based innovation—the policy interest in developing the local endowments, institutions, and interactions required of dynamic innovation ecosystems—places new demands on data that federal collections were never designed to satisfy. To date, local measures of innovation incidence have relied on patent data that is available at the county level. However, patents are a weak innovation indicator as not all innovations are patentable; firms may prefer other means of intellectual property protection even for patentable inventions; and distinctions between product, process, and business practice innovation are usually unavailable. Innovation data collected in the Annual Business Survey (ABS) address all these weaknesses but are too sparse to provide accurate estimates of innovation incidence for all but the largest metropolitan areas. This project will investigate the feasibility of using the much larger Economic Census (EC) that contains no innovation data to substantially increase the number of firms in a small area to produce more accurate innovation rate estimates. This is done by predicting innovation behavior of firms in the EC from variables that are also included in the ABS, using a technique called small area estimation. This method “borrows strength” from a much larger general dataset (EC) to enhance the predictive power of a smaller, more detailed dataset (ABS). It is regularly used to produce local estimates of phenomena of policy interest that would be prohibitively expensive to collect, such as disease incidence or childhood poverty rates. This project is the first time these techniques have been applied to innovation data.<br/><br/>The goal of this project is to generate the Small Area Innovation Rate Estimation (SAIRE). Preliminary analysis using the ABS has found that commonly used control variables such as industry sector, firm size category, or state where the firm is located are predictive of innovation behavior and would be an improvement over naïve local area estimates. The project will investigate possible increases in efficiency by replacing the fixed effects used in the preliminary analysis with random effects in a generative Bayesian multilevel model. In addition to expected increases in efficiency from aspatial pooling provided by a random effects specification, estimation of innovation phenomena may be improved by modeling spatial dependence across proximate small areas. More precise innovation rate estimates may be possible by adding other firm or local characteristics into the predictive model such as cloud computing or local human capital endowments. The two major methodological challenges presented by the research are 1) incorporating complex sample design in the small area estimation as the probability of selection and innovation may be dependent on the same variables such as firm size; and 2) assessing the extent to which firm-level variables in ABS are predictive of establishment-level innovation in EC for multi-unit firms. Accurate meso-level measures of SAIRE would inform the targeting and evaluation of place-based innovation initiatives such as the Regional Innovation Engines program as well as addressing questions such as the role of innovation in reallocation growth that cannot be analyzed using current microdata.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/09/2024
|
07/09/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2430913
|
[{'FirstName': 'Zheng', 'LastName': 'Tian', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zheng Tian', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A05KK', 'StartDate': '07/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Stephan', 'LastName': 'Goetz', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Stephan J Goetz', 'EmailAddress': '[email protected]', 'NSF_ID': '000332572', 'StartDate': '07/09/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Pennsylvania State Univ University Park', 'CityName': 'UNIVERSITY PARK', 'ZipCode': '168021503', 'PhoneNumber': '8148651372', 'StreetAddress': '201 OLD MAIN', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '15', 'CONGRESS_DISTRICT_ORG': 'PA15', 'ORG_UEI_NUM': 'NPM2J7MSCF61', 'ORG_LGL_BUS_NAME': 'THE PENNSYLVANIA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Pennsylvania State Univ University Park', 'CityName': 'UNIVERSITY PARK', 'StateCode': 'PA', 'ZipCode': '168021503', 'StreetAddress': '201 OLD MAIN', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '15', 'CONGRESS_DISTRICT_PERF': 'PA15'}
|
{'Code': '301Y00', 'Text': 'NSF Engines - Type 2'}
|
2024~299998
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430913.xml'}
|
ENG-QUANT: Metamaterial-enabled superconducting nanowire detectors for high temperature operation
|
NSF
|
10/01/2024
|
09/30/2027
| 330,000 | 330,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Supriyo Bandyopadhyay', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032925392'}
|
ENG-QUANT: Metamaterial-enabled superconducting nanowire detectors for high temperature operation<br/><br/>Single-photon detectors are at the core of modern strategic quantum technologies. Superconducting nanowire single-photon detectors offer outstanding, unbeaten counting performances at near-infrared; however, their sub-Kelvin operation requires bulky and expensive cryostat, hindering their widespread field deployment and representing one of the obstacles to the large-scale diffusion and democratization of photonic quantum technologies. To solve this bottleneck, this proposal aims to increase the operational temperature of these detectors by exploring superconducting, optical, and thermal metamaterials combined in novel device architectures while using traditional superconducting compounds available for large-scale fabrication. The proposed research, if successful, will not only result in nanowire single-photon detectors operating a ~10 Kelvin for near-to-mid-infrared wavelengths but extend superconducting technology's applicability, making it accessible to more researchers and broadening the scope of quantum research and applications beyond the elite confines of current technology. This research project will train one graduate student in the wide area of quantum hardware, provide opportunities for the early involvement of undergraduate researchers, specifically from underrepresented groups, and will have a significant educational impact, with the development of teaching modules on several topics. <br/><br/>The approach of this project is to develop high-temperature, highly efficient near-to-mid-infrared nanowire detectors through the integration of metamaterials. The theory of single-photon detection in nanowires suggests that efficient detection can be achieved at high temperatures if nanowires can reach the true superconducting depairing state. The proposed research specifically targets this objective and supports high-temperature detection by developing and integrating three nanostructured metamaterials. (1) A superconducting metamaterial capable of reaching the superconducting depairing limit at high temperature, based on nanowires fabricated from optimized high critical temperature type-II thin-film, featuring topography tuning for homogenous switching currents, vortex engineering for controlled pinning and reduced entry, and fabrication process optimization for reduced roughness. (2) An optical metamaterial to support high external efficiency based on nanowire-integrated plasmonic nanostructures metamaterials. (3) A thermal metamaterial to foster high-temperature detection capabilities by enhancing high-energy down-converted phonons injection and recovery. Finally, the three metamaterials will be integrated into a single architecture to demonstrate high-efficiency single-photon detectors operating at high temperatures. Beyond quantum technologies, the successful completion of the project will impact various other applications, from astronomy to biomedical imaging.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/01/2024
|
08/01/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430923
|
[{'FirstName': 'Marco', 'LastName': 'Colangelo', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Marco Colangelo', 'EmailAddress': '[email protected]', 'NSF_ID': '000810775', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Matteo', 'LastName': 'Rinaldi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Matteo Rinaldi', 'EmailAddress': '[email protected]', 'NSF_ID': '000607193', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Benyamin', 'LastName': 'Davaji', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Benyamin Davaji', 'EmailAddress': '[email protected]', 'NSF_ID': '000829452', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'ZipCode': '021155005', 'PhoneNumber': '6173733004', 'StreetAddress': '360 HUNTINGTON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'HLTMVS2JZBS6', 'ORG_LGL_BUS_NAME': 'NORTHEASTERN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'StateCode': 'MA', 'ZipCode': '021155005', 'StreetAddress': '360 HUNTINGTON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}
|
{'Code': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}
|
2024~330000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430923.xml'}
|
SBIR Phase I: Upcycling waste plastics into high value thermoplastic elastomer
|
NSF
|
09/01/2024
|
02/28/2025
| 274,991 | 274,991 |
{'Value': 'Standard Grant'}
|
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
|
{'SignBlockName': 'Rajesh Mehta', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922174'}
|
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is in the development of a sustainable solution to the global problem of plastic waste. Currently, over 90% of plastics ever produced still exist in the environment, posing significant threats to ecosystems and human health. This project aims to transform waste plastics into valuable materials that can be used in infrastructure applications, such as road construction. By recycling non-recyclable plastics into high-performance elastomers, this project not only reduces the environmental impact of plastic waste but also enhances the durability and longevity of pavements. The commercial impact includes the creation of new jobs in the recycling and construction industries, generating tax revenue, and contributing to a more sustainable economy. This project aligns with NSF's mission to promote scientific progress and support innovations that address societal challenges, ultimately improving the quality of life for U.S. citizens.<br/><br/><br/>The strong technical innovation in this project is the use of Reversible Addition-Fragmentation Chain Transfer (RAFT) polymerization to produce high-value elastomers from depolymerized plastic oligomers. This method allows for precise control over the polymerization process, resulting in materials with superior mechanical properties compared to traditional recycling methods. The research will explore the optimal conditions for depolymerizing waste plastics and subsequently polymerizing them into elastomers suitable for infrastructure applications. The goals of this project include demonstrating the feasibility of this approach, optimizing the material properties for pavement use, and conducting performance testing to validate the effectiveness of the produced elastomers. The methods involve a combination of laboratory experiments, material characterization, and mechanical testing to ensure the produced elastomers meet industry standards for durability and performance. This innovative approach has the potential to revolutionize the recycling of plastics and contribute to the development of sustainable infrastructure materials.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/26/2024
|
08/26/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2430937
|
{'FirstName': 'Shelly', 'LastName': 'Zhang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shelly Zhang', 'EmailAddress': '[email protected]', 'NSF_ID': '000991179', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'MOLTEN MATERIALS LLC', 'CityName': 'SANTA ANA', 'ZipCode': '927054511', 'PhoneNumber': '3238131233', 'StreetAddress': '1269 S WRIGHT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '46', 'CONGRESS_DISTRICT_ORG': 'CA46', 'ORG_UEI_NUM': 'V8JSL5SD4QV3', 'ORG_LGL_BUS_NAME': 'MOLTEN MATERIALS LLC', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'MOLTEN MATERIALS LLC', 'CityName': 'SANTA ANA', 'StateCode': 'CA', 'ZipCode': '927054511', 'StreetAddress': '1269 SOUTH WRIGHT STREET', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '46', 'CONGRESS_DISTRICT_PERF': 'CA46'}
|
{'Code': '537100', 'Text': 'SBIR Phase I'}
|
2024~274991
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430937.xml'}
|
ENG-QUANT: EPCN:Small: Quantum information control: A foundation for quantum inference
|
NSF
|
09/01/2024
|
08/31/2027
| 545,300 | 545,300 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Eyad Abed', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922303'}
|
Quantum inference is essential to unleashing full quantum advantage in sensing, communication, and computing. Quantum inference relies on measurements facilitated by quantum control; however, inference and control are traditionally treated separately in the design and analysis of quantum systems. This research puts forth a new vision and unifying framework, referred to as quantum information control, in which control of statistical information serves as a foundation for ultra-precise quantum inference. At the intersection of quantum information, statistical inference, and control theory, this research is a cross-pollination of traditionally disparate scientific fields, thus constituting a unique opportunity to capitalize on the strengths of each field and produce transformative theories and algorithms. This work will facilitate the maturation of emerging quantum information platforms.<br/><br/>Quantum information control centers on modeling and controlling statistical information (e.g., Fisher information) to improve inference capabilities (e.g., the accuracy of parameter estimation) in real-world open quantum systems, which are subject to environmental noise and practical design constraints. The goals of this project are to: (i) establish a framework for characterizing the time evolution of controlled statistical information; (ii) derive the ultimate performance limits of quantum information control; and (iii) develop control algorithms approaching these limits. Inspired by concepts in statistical inference, the notion of admissible controls-independent of the parameters they elicit-is introduced. A class of theorems will be developed to identify when information maximizing controls are admissible and hence realizable in practice. Moreover, near-optimal adaptive control algorithms will be designed for situations in which the admissibility conditions are not met. Central to this project is the concept of time-dependent reachable sets of measurement operators. Such reachable sets will be characterized and information extraction will be optimized over them to establish tight information inequalities. The multidisciplinary approach developed in this fundamental research will lay the foundations for quantum information control, paving the way to unparalleled capabilities for quantum sensing, communication, and computing.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/30/2024
|
07/30/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430953
|
{'FirstName': 'Moe', 'LastName': 'Win', 'PI_MID_INIT': 'Z', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Moe Z Win', 'EmailAddress': '[email protected]', 'NSF_ID': '000370320', 'StartDate': '07/30/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Massachusetts Institute of Technology', 'CityName': 'CAMBRIDGE', 'ZipCode': '021394301', 'PhoneNumber': '6172531000', 'StreetAddress': '77 MASSACHUSETTS AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'E2NYLCDML6V1', 'ORG_LGL_BUS_NAME': 'MASSACHUSETTS INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': 'E2NYLCDML6V1'}
|
{'Name': 'Massachusetts Institute of Technology', 'CityName': 'CAMBRIDGE', 'StateCode': 'MA', 'ZipCode': '021394301', 'StreetAddress': '77 MASSACHUSETTS AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}
|
{'Code': '760700', 'Text': 'EPCN-Energy-Power-Ctrl-Netwrks'}
|
2024~545300
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430953.xml'}
|
CAREER: Enabling Trustworthy Speech Technologies for Mental Health Care: From Speech Anonymization to Fair Human-centered Machine Intelligence
|
NSF
|
01/01/2024
|
08/31/2026
| 600,000 | 451,747 |
{'Value': 'Continuing Grant'}
|
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
|
{'SignBlockName': 'Wendy Nilsen', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922568'}
|
Speech-based technologies have been heralded as promising solutions to overcome the limitations of existing clinical modalities related to limited healthcare access, non-naturalistic in-clinic interactions, and social stigma. Speech measures combined with artificial intelligence can serve as valuable biomarkers for mental health conditions, such as depression and post-traumatic stress disorder. Yet, in order for artificial intelligence to truly succeed in a future-of-work landscape in which clinicians will be expected to work side-by-side with artificial intelligence systems, both clinicians and patients need to calibrate their trust in the algorithms that power this decision-making process. The goal of this project is to design reliable machine learning, notably for speech-based diagnosis and monitoring of mental health, for addressing three pillars of trustworthiness: explainability, privacy preservation, and fair decision making. Trustworthiness is critical for both patients and clinicians: patients must be treated fairly and without the risk of reidentification, while clinical decision-making needs to rely on explainable and unbiased machine learning. This research program further provides a fertile ground for training high school and college students providing them with the knowledge about (and inclination toward) ethically applying computing research in sensitive populations. The tangible applications developed as part of this research serve as a vehicle to encourage students to pursue careers in Science, Technology, Engineering, and Mathematics, and prepare them to work in transdisciplinary settings for solving real-world problems.<br/><br/>This project seeks to design explainable, anonymized, and fair speech biomarkers for mental health, integrating aspects of speech acquisition, transparent modeling, and unbiased decision making. The work is divided into three technical objectives. The first objective designs novel speaker anonymization algorithms that retain mental health information and suppress information related to the identity of the speaker. The anonymization algorithms learn a mapping between the original speech and a latent space, which embeds information about speaker identity, mental health, and phonological sequence through deterministic and probabilistic operations. The second objective improves explainability of speech-based models for tracking mental health through novel convolutional architectures that learn explainable spectrotemporal transformations relevant to speech production fundamentals. The third objective examines how bias in data and model design may perpetuate social disparities in mental health, and designs new machine learning to mitigate unwanted bias in speech-based mental health diagnosis. Through a series of experiments this work further contributes to understanding ways in which human-machine partnerships are formed in mental healthcare settings along dimensions of trust formation, maintenance, and repair.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
06/12/2024
|
08/16/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430958
|
{'FirstName': 'Theodora', 'LastName': 'Chaspari', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Theodora Chaspari', 'EmailAddress': '[email protected]', 'NSF_ID': '000760286', 'StartDate': '06/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Colorado at Boulder', 'CityName': 'Boulder', 'ZipCode': '803090001', 'PhoneNumber': '3034926221', 'StreetAddress': '3100 MARINE ST', 'StreetAddress2': 'STE 481 572 UCB', 'CountryName': 'United States', 'StateName': 'Colorado', 'StateCode': 'CO', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'CO02', 'ORG_UEI_NUM': 'SPVKK1RC2MZ3', 'ORG_LGL_BUS_NAME': 'THE REGENTS OF THE UNIVERSITY OF COLORADO', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Colorado at Boulder', 'CityName': 'Boulder', 'StateCode': 'CO', 'ZipCode': '803090001', 'StreetAddress': '3100 MARINE ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Colorado', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'CO02'}
|
{'Code': '736400', 'Text': 'Info Integration & Informatics'}
|
['2021~93650', '2022~115496', '2023~119316', '2024~123285']
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430958.xml'}
|
Student Support for International Solid Freeform Fabrication (SFF 2024) Symposium; Austin, Texas; 11-14 August 2024
|
NSF
|
08/01/2024
|
07/31/2025
| 48,025 | 48,025 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Linkan Bian', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928136'}
|
This grant supports student participation at the Thirty-Fifth Annual International Solid Freeform Fabrication (SFF) Symposium, scheduled for 11-14 August 2024, in Austin, Texas. The SFF Symposium serves as a venue for the exchange of knowledge in the realms of additive, freeform, and hybrid manufacturing. Last year, the event drew participants from over 100 universities, with 70% representing domestic institutions. Notably, student attendees constituted approximately 45% of the 700+ total participants. The 2024 symposium will emphasize new developments in eco-friendly manufacturing processes and the integration of artificial intelligence in additive manufacturing. Additionally, a special session on biomedical applications of additive manufacturing will be featured to enhance interdisciplinary research and collaborations within the field. This year's symposium also features the introduction of a mentoring program, designed to match each student with a mentor from industry, national labs, or academia based on their career goals and interests. This initiative aims to provide personalized guidance and enhance career development opportunities for participants. To foster accessibility and encourage diverse student attendance, the travel award will help cover conference registration fees, accommodations, and travel expenses for qualified students. This initiative aims to lower barriers to entry and ensure a broad representation of ideas. <br/><br/>Outreach for student support applications will include: (1) direct emails to authors of accepted abstracts, (2) targeted communications to past SFF attendees, (3) announcements on the SFF website, and (4) social media campaigns on platforms like LinkedIn. The selection process, conducted by the conference committee, will prioritize students from U.S. institutions who are actively contributing to the conference through presentations, posters, or participation in competitions. Special consideration is given to students attending for the first time, as part of a commitment to broadening participation and engaging new members of the community. Student awardees will also benefit from exclusive networking opportunities, including a luncheon panel that discusses current research trends and potential career paths in additive manufacturing. This award aims to equip emerging leaders with a comprehensive global outlook, exposure to innovative ideas, and insight into future industry challenges.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/24/2024
|
07/24/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430975
|
{'FirstName': 'Maryam', 'LastName': 'Tilton', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Maryam Tilton', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A06HL', 'StartDate': '07/24/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Texas at Austin', 'CityName': 'AUSTIN', 'ZipCode': '787121139', 'PhoneNumber': '5124716424', 'StreetAddress': '110 INNER CAMPUS DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'TX25', 'ORG_UEI_NUM': 'V6AFQPN18437', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF TEXAS AT AUSTIN', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Texas at Austin', 'CityName': 'AUSTIN', 'StateCode': 'TX', 'ZipCode': '787121139', 'StreetAddress': '110 INNER CAMPUS DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_PERF': 'TX25'}
|
{'Code': '088Y00', 'Text': 'AM-Advanced Manufacturing'}
|
2024~48025
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430975.xml'}
|
Conference: Cosmovisions of the Pacific: Advancing Indigenous - non-Indigenous Collaboration with Integrity (Cosmovisions)
|
NSF
|
08/01/2024
|
04/30/2025
| 49,965 | 49,965 |
{'Value': 'Standard Grant'}
|
{'Code': '01090000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OISE', 'LongName': 'Office Of Internatl Science &Engineering'}}
|
{'SignBlockName': 'Allen Pope', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928030'}
|
Cosmovisions of the Pacific will bring together ~20 Indigenous and non-Indigenous knowledge holders, researchers, educators and other persons interested in establishing a more formal network of collaborators and in the co-creation of guiding principles necessary for collaboration with integrity across cultures. Recently, we’ve seen the cost of cross-cultural conflict as exemplified by protests against the construction of the Thirty-Meter Telescope in Hawaii, the Keystone XL (KXL) pipeline project, and elsewhere. As big science and commercial endeavors require more robust collaborations between Indigenous and non-Indigenous groups, we must find ways of understanding, working and communicating across cultures and ways of knowing. Cosmovisions will deeply explore Indigenous and non-Indigenous knowledge building using a participatory design approach. This will include a 3-day Gathering and preparation where participants engage in deep conversations about differing approaches to research questions and scenarios, network building activities, and presentations that uncover the similarities and differences in approaches to knowledge building across Indigenous and non-Indigenous cultures. The strategic objectives for work proposed to be delivered in a post-Gathering report include: Identifying priority opportunities for Indigenous - non-Indigenous collaboration, developing recommendations that will help guide successful Indigenous and non- Indigenous collaboration, and developing and initial network of Indigenous and non-Indigenous researchers, educators, knowledge holders and others who are committed to collaboration across cultures and ways of knowing.<br/><br/>The Cosmovisions Gathering agenda will be developed based on a formalized framework which are centered around empowerment, reframing, engaging critically, allowing Indigenous people to set the agenda, and integrating ways of knowing. This project is intentionally and deeply interdisciplinary. As “cosmovisions” are worldviews by which various individuals and cultures connect with the universe around them, the workshop will have a co-created structure going into the Gathering, but allow for flexibility and generative outcomes. Cosmovisions will create a space where through authentic collaboration, Indigenous persons can more fully engage, benefit, and engage with non-Indigenous STEM practitioners. In addition, through dissemination efforts including potential future gatherings and a post-Gathering report, the broader STEM community and society more generally, will come to understand and benefit from the “two-eyed” seeing approach to knowledge building.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
06/21/2024
|
06/21/2024
|
None
|
Grant
|
47.079
|
1
|
4900
|
4900
|
2430977
|
[{'FirstName': 'YASMIN', 'LastName': 'CATRICHEO', 'PI_MID_INIT': 'V', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'YASMIN V CATRICHEO', 'EmailAddress': '[email protected]', 'NSF_ID': '000826252', 'StartDate': '06/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Anica', 'LastName': 'Miller-Rushing', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Anica Miller-Rushing', 'EmailAddress': '[email protected]', 'NSF_ID': '000994108', 'StartDate': '06/21/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Associated Universities, Inc.', 'CityName': 'VIENNA', 'ZipCode': '221807300', 'PhoneNumber': '2024621676', 'StreetAddress': '2650 PARK TOWER DR STE 700', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_ORG': 'VA11', 'ORG_UEI_NUM': 'NZBMKZMW68N3', 'ORG_LGL_BUS_NAME': 'ASSOCIATED UNIVERSITIES INC', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Associated Universities, Inc.', 'CityName': 'VIENNA', 'StateCode': 'VA', 'ZipCode': '221807300', 'StreetAddress': '2650 PARK TOWER DR STE 700', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_PERF': 'VA11'}
|
{'Code': '069Y00', 'Text': 'AccelNet - Accelerating Resear'}
|
2024~49965
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430977.xml'}
|
SCC-CIVIC-PG Track B: Night Moves - Enhancing Mobility Accessibility and Safety for Night Shift Workers in Baltimore, Maryland
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'David Corman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928754'}
|
Night shift workers play a crucial role in a continuously operating economy. However, they also encounter unique challenges such as limited transportation options and increased safety risks during nighttime hours. These issues are particularly pronounced in Baltimore City, Maryland, which grapples with crime rates in the evening, inadequate nighttime transit coverage, and mismatches between job locations and residential areas for night shift workers. The recent collapse of the Francis Scott Key Bridge has exacerbated commuting pressures further. The primary objective of this CIVIC Stage 1 award is to improve mobility and safety for night shift workers in Baltimore. This project will investigate the mobility and safety needs of nigh workers and the spatial job mismatch problem in Baltimore. By working closely with local communities, transportation authorities, and the local mobility industry, this project will identify effective and sustainable solutions, such as redesigning transit routes, adjusting schedules to meet nighttime demand and exploring flexible transportation services. <br/><br/>In Baltimore City, Maryland, persistent high crime rates, particularly at night, present significant challenges for night shift workers, especially in economically disadvantaged neighborhoods. This issue is compounded by a spatial mismatch between the locations of night-shift jobs and residential areas, which restricts mobility options and heightens vulnerability to crime, exacerbated further by the recent collapse of the Francis Scott Key Bridge. To address these issues, our objectives are fourfold: first, to investigate the spatial mismatch problem in Baltimore City, focusing on night shift jobs; second, to analyze the mobility needs of night workers and develop a tool to assess vulnerability in high-risk areas; third, to identify deficiencies in public mobility services and support Maryland Transit Administration (MTA) in improving transit systems, while exploring alternative transportation solutions; and finally, to cultivate partnerships with local industries to enhance public transport options as necessary.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/12/2024
|
08/12/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2430978
|
[{'FirstName': 'Mansoureh', 'LastName': 'Jeihani', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mansoureh Jeihani', 'EmailAddress': '[email protected]', 'NSF_ID': '000588874', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Xianfeng', 'LastName': 'Yang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xianfeng Yang', 'EmailAddress': '[email protected]', 'NSF_ID': '000715027', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Yiqun', 'LastName': 'Xie', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yiqun Xie', 'EmailAddress': '[email protected]', 'NSF_ID': '000838452', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Di', 'LastName': 'Yang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Di Yang', 'EmailAddress': '[email protected]', 'NSF_ID': '000922446', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'ZipCode': '207425100', 'PhoneNumber': '3014056269', 'StreetAddress': '3112 LEE BUILDING', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MD04', 'ORG_UEI_NUM': 'NPU8ULVAAS23', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MARYLAND, COLLEGE PARK', 'ORG_PRNT_UEI_NUM': 'NPU8ULVAAS23'}
|
{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'StateCode': 'MD', 'ZipCode': '207425100', 'StreetAddress': '3112 LEE BUILDING', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'MD04'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430978.xml'}
|
Collaborative Research: ENG-SEMICON: Merging Electrostatic and Ferroelectric MEMS Actuators to Create Tunable High-Speed Scanners
|
NSF
|
09/01/2024
|
08/31/2027
| 275,000 | 275,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Richard Nash', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032925394'}
|
This project aims to create micro-mirrors for applications in endoscopes that enable controlling the depth-of-focus and imaging in real-time. These instruments can guide surgeries to distinguish normal and malignant tissues with sub-cellular resolution. State-of-the-art endomicroscopy utilizes MEMS scanning mirrors for single-axis and dual-axis confocal microscopy. However, the depth of focus and scanning speed are severely limited because of the actuation mechanism. The most common actuators have been based on conventional electrostatic mechanisms that face two bottlenecks: small range of motion and limited speed. The team of investigators will overcome those limitations by using electrostatic levitation that enables large strokes away from the substrate. To enable high-speed scanning, investigators will adopt ferroelectric material to control spring stiffnesses. This property enables achieving a wide range of scanning speeds at any elevation. The large range of motion because of electrostatic levitation, and stiffness tunability using ferroelectric material will permit the development of tunable MEMS scanners that can revolutionize endomicroscopy for real-time in vivo imaging and 3D depth sensing. The new microscanner increases the depth of focus and enables deep tissue penetration over a large FOV with sub-cellular resolution. To educate a wide range of learners, the investigators develop workshops for demonstrating the basics of micromirrors and present them to elementary schools as well as undergraduate students. Investigators will involve undergraduate students from a diverse group of students, including underrepresented minorities. <br/><br/>This project will create new knowledge on the interaction of electrostatic levitation with ferroelectric polarization switching. Based on this new knowledge, investigators will create tunable high-speed and large-stroke MEMS mirrors. For more than forty years, MEMS mirrors for imaging applications have been based on conventional gap-closing mechanisms that severely suffer from a limited range of motion and pull-in instability. To address those issues, a team of researchers will introduce electrostatic levitation electrodes that allow the actuator to move away from the substrate and have its motion become a linear function of applied voltage. To achieve tunable high-speed actuation, the team will incorporate springs made of integrated ferroelectric material that enables stiffness tuning to trigger modes of interest, e.g., titling or out-of-plane at desired frequencies. The merger of electrostatic levitation and ferroelectric polarization switching creates challenging behaviors that have prevented researchers from adopting it for micro-mirror applications. Investigators will present a computational, analytical, and experimental platform to present a fundamental understating of the underlying multiphysics of the system. In addition, the team will create a MEMS mirror that achieves high-speed large strokes and rotations from four actuators on its periphery. The micromirror prototype will pave the way for its future application in real-time in vivo microendoscopy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/12/2024
|
08/12/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430981
|
{'FirstName': 'Shahrzad', 'LastName': 'Towfighian', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shahrzad Towfighian', 'EmailAddress': '[email protected]', 'NSF_ID': '000658154', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'SUNY at Binghamton', 'CityName': 'BINGHAMTON', 'ZipCode': '139024400', 'PhoneNumber': '6077776136', 'StreetAddress': '4400 VESTAL PKWY E', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_ORG': 'NY19', 'ORG_UEI_NUM': 'NQMVAAQUFU53', 'ORG_LGL_BUS_NAME': 'RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK, THE', 'ORG_PRNT_UEI_NUM': 'GMZUKXFDJMA9'}
|
{'Name': 'SUNY at Binghamton', 'CityName': 'BINGHAMTON', 'StateCode': 'NY', 'ZipCode': '139024400', 'StreetAddress': '4400 VESTAL PKWY E', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_PERF': 'NY19'}
|
{'Code': '756400', 'Text': 'CCSS-Comms Circuits & Sens Sys'}
|
2024~275000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430981.xml'}
|
Collaborative Research: ENG-SEMICON: Merging Electrostatic and Ferroelectric MEMS Actuators to Create Tunable High-Speed Scanners
|
NSF
|
09/01/2024
|
08/31/2027
| 275,000 | 275,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Richard Nash', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032925394'}
|
This project aims to create micro-mirrors for applications in endoscopes that enable controlling the depth-of-focus and imaging in real-time. These instruments can guide surgeries to distinguish normal and malignant tissues with sub-cellular resolution. State-of-the-art endomicroscopy utilizes MEMS scanning mirrors for single-axis and dual-axis confocal microscopy. However, the depth of focus and scanning speed are severely limited because of the actuation mechanism. The most common actuators have been based on conventional electrostatic mechanisms that face two bottlenecks: small range of motion and limited speed. The team of investigators will overcome those limitations by using electrostatic levitation that enables large strokes away from the substrate. To enable high-speed scanning, investigators will adopt ferroelectric material to control spring stiffnesses. This property enables achieving a wide range of scanning speeds at any elevation. The large range of motion because of electrostatic levitation, and stiffness tunability using ferroelectric material will permit the development of tunable MEMS scanners that can revolutionize endomicroscopy for real-time in vivo imaging and 3D depth sensing. The new microscanner increases the depth of focus and enables deep tissue penetration over a large FOV with sub-cellular resolution. To educate a wide range of learners, the investigators develop workshops for demonstrating the basics of micromirrors and present them to elementary schools as well as undergraduate students. Investigators will involve undergraduate students from a diverse group of students, including underrepresented minorities. <br/><br/>This project will create new knowledge on the interaction of electrostatic levitation with ferroelectric polarization switching. Based on this new knowledge, investigators will create tunable high-speed and large-stroke MEMS mirrors. For more than forty years, MEMS mirrors for imaging applications have been based on conventional gap-closing mechanisms that severely suffer from a limited range of motion and pull-in instability. To address those issues, a team of researchers will introduce electrostatic levitation electrodes that allow the actuator to move away from the substrate and have its motion become a linear function of applied voltage. To achieve tunable high-speed actuation, the team will incorporate springs made of integrated ferroelectric material that enables stiffness tuning to trigger modes of interest, e.g., titling or out-of-plane at desired frequencies. The merger of electrostatic levitation and ferroelectric polarization switching creates challenging behaviors that have prevented researchers from adopting it for micro-mirror applications. Investigators will present a computational, analytical, and experimental platform to present a fundamental understating of the underlying multiphysics of the system. In addition, the team will create a MEMS mirror that achieves high-speed large strokes and rotations from four actuators on its periphery. The micromirror prototype will pave the way for its future application in real-time in vivo microendoscopy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/12/2024
|
08/12/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430982
|
{'FirstName': 'Benyamin', 'LastName': 'Davaji', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Benyamin Davaji', 'EmailAddress': '[email protected]', 'NSF_ID': '000829452', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'ZipCode': '021155005', 'PhoneNumber': '6173733004', 'StreetAddress': '360 HUNTINGTON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'HLTMVS2JZBS6', 'ORG_LGL_BUS_NAME': 'NORTHEASTERN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'StateCode': 'MA', 'ZipCode': '021155005', 'StreetAddress': '360 HUNTINGTON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}
|
{'Code': '756400', 'Text': 'CCSS-Comms Circuits & Sens Sys'}
|
2024~275000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430982.xml'}
|
CIVIC-PG Track B: Advancing Health Equity in Western Kansas Rural Communities Affected by Gender-Based Violence: A Survivor-Centered Advocacy Approach
|
NSF
|
10/01/2024
|
03/31/2025
| 74,446 | 74,446 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Sara Kiesler', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928643'}
|
Gender-based violence is a pervasive public health issue, particularly in rural communities where access to support services is often limited. This project aims to address these gaps in health equity for survivors by implementing survivor-centered interventions that mobilize existing community resources, identify local leaders, and enhance economic opportunities and employment. The primary focus of this project is creating a network of support by empowering local leaders and volunteers who can connect organizations and other community members and networks. This approach will help build collaborative and coordinated responses to survivors that address immediate needs and promote long-term stability and independence. The project is also developing community-based support groups to improve access to healthcare, financial assistance, and housing support. The ultimate aim is to generate solutions that can be scaled and adapted to similar settings nationwide, fostering organizational connections and creating pathways for financial stability. This project aligns with NSF’s mission to promote the progress of science, engineering, and education by contributing to broader research on health equity and violence prevention.<br/><br/>The primary goal of this project is to develop and implement participant action-oriented and survivor-centered interventions to improve health equity for gender-based violence survivors in rural communities. In Stage 1, the team is conducting extensive stakeholder consultations, listening sessions, and community engagement activities to gather insights and identify key community leaders and civic partners. It is mobilizing community resources to identify facilitators, including local leaders and volunteers, who can connect organizations, individuals, and community leaders, fostering ongoing collaboration. It is forming a volunteer task force and establishing a community leader forum to better utilize local resources. Employment training, apprenticeship programs, and financial assistance initiatives are planned to support survivors’ economic independence. These efforts will culminate in a Stage 2 project aimed at creating a collaboration across providers, nonprofits, and volunteers, and a health equity assessment toolkit, utilizing the information gathered in Stage 1 to further enhance health equity in rural communities.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track B. Bridging the gap between essential resources and services & community needs and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/08/2024
|
08/08/2024
|
None
|
Grant
|
47.070, 47.075
|
1
|
4900
|
4900
|
2430996
|
[{'FirstName': 'Ziwei', 'LastName': 'Qi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ziwei Qi', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A05TJ', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Naishuo', 'LastName': 'Sun', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Naishuo Sun', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A05V6', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Rachel', 'LastName': 'Dolechek', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rachel Dolechek', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A05ZY', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Fort Hays State University', 'CityName': 'HAYS', 'ZipCode': '676014009', 'PhoneNumber': '7856284338', 'StreetAddress': '600 PARK ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Kansas', 'StateCode': 'KS', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'KS01', 'ORG_UEI_NUM': 'DVSMS2BMAK51', 'ORG_LGL_BUS_NAME': 'FORT HAYS STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'L6NFSNHUEKC1'}
|
{'Name': 'Fort Hays State University', 'CityName': 'HAYS', 'StateCode': 'KS', 'ZipCode': '676014009', 'StreetAddress': '600 PARK ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Kansas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'KS01'}
|
[{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}, {'Code': '164000', 'Text': 'Information Technology Researc'}]
|
2024~74446
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430996.xml'}
|
EAGER:TaskDCL: Neuroadaptive Context-Aware Human-Robot Collaboration: Mitigating Surgeons' Mental Overload in Robotic-Assisted Surgery
|
NSF
|
09/01/2024
|
08/31/2026
| 300,000 | 300,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Alexandra Medina-Borja', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927557'}
|
Robotic-assisted surgery has the potential to offer enhanced overall surgical performance and greater precision compared to traditional surgical methods. However, surgeons’ mental workload remains a concern in robotic-assisted surgery due to increased complexity of operations, leading to unexpected human errors and unsatisfactory surgical outcomes. As robotic-assisted surgery rapidly advances with more complex technology, it is critical to prevent surgeons’ mental overload to ensure surgical task performance and patient safety. Neuro-adaptive technology represents an innovative solution for reducing human mental workload by enabling the context-awareness of robots to offer adaptive interventions within response to variations in human cognitive states. However, the adoption of the neuro-adaptive technology in robotic-assisted surgery remains largely unexplored. This gap highlights a fundamental research opportunity in understanding the advantages and limitations of neuro-adaptive technology to enhance surgical outcomes. This EArly-concept Grant for Exploratory Research (EAGER) grant supports research to design neuro-adaptive technology for robotic-assisted surgery. Introducing such an innovative technology to robotic-assisted surgery has the potential to transform traditional teleoperation into a more collaborative human-robot interaction. This, in turn, has the potential to improve patient health, identify and mitigate cognitively demanding procedures or operative conditions, and to reduce costs associated with adverse patient outcomes.<br/><br/>This research aims to design neuro-adaptive robotic-assisted surgery by enabling the robot's awareness of the surgical context, with the aim of understanding: (1) how to monitor different surgeons’ workload levels, (2) how to understand the cause of such workload, and (3) how to perform interventions. An artificial intelligence-powered multi-sensing system will be investigated to monitor workload levels on a personal basis for surgeons with varying skill levels. A context-awareness architecture that synthesizes visual and auditory data will be used to identify the cause of mental overload and initiate proper interventions and a prototype of the researched neuro-adaptive technology will be designed and validated. By leveraging multi-modal sensor data, human factors modeling, and artificial intelligence, the ultimate goal of this project is to refine the implementation of these life-saving remote surgery techniques, ensuring that they are more effective, adaptable, and safe.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2430998
|
[{'FirstName': 'Xiaoyu', 'LastName': 'Chen', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xiaoyu Chen', 'EmailAddress': '[email protected]', 'NSF_ID': '000915858', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jing', 'LastName': 'Yang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jing Yang', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A05Y1', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'SUNY at Buffalo', 'CityName': 'AMHERST', 'ZipCode': '142282577', 'PhoneNumber': '7166452634', 'StreetAddress': '520 LEE ENTRANCE STE 211', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '26', 'CONGRESS_DISTRICT_ORG': 'NY26', 'ORG_UEI_NUM': 'LMCJKRFW5R81', 'ORG_LGL_BUS_NAME': 'RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK, THE', 'ORG_PRNT_UEI_NUM': 'GMZUKXFDJMA9'}
|
{'Name': 'SUNY at Buffalo', 'CityName': 'AMHERST', 'StateCode': 'NY', 'ZipCode': '142602050', 'StreetAddress': '319 Bell Hall', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '26', 'CONGRESS_DISTRICT_PERF': 'NY26'}
|
[{'Code': '058Y00', 'Text': 'M3X - Mind, Machine, and Motor'}, {'Code': '164200', 'Text': 'Special Initiatives'}]
|
2024~300000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2430998.xml'}
|
Glycocalyx Engineering to Probe Mucin Signal Transduction
|
NSF
|
09/01/2024
|
08/31/2027
| 543,251 | 543,251 |
{'Value': 'Standard Grant'}
|
{'Code': '03090000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'CHE', 'LongName': 'Division Of Chemistry'}}
|
{'SignBlockName': 'Pumtiwitt McCarthy', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032920000'}
|
With the support of the Chemistry of Life Processes (CLP) program in the Division of Chemistry, Professor Jessica Kramer of the University of Utah is studying the development of cellular glycocalyx models to understand processes that regulate cell growth and survival. The glycocalyx is a protein and sugar coating on the surface of cells. In locations such as the eyes, lungs, gastrointestinal and reproductive tract, the glycocalyx is rich in mucin proteins, which are also found in mucus. The mucin glycocalyx has complex biological functions and diverse roles in health and disease but has not been systematically studied at the chemical level. Through the course of this project, the PI seeks to create chemically tunable models of the glycocalyx and apply them to study cellular pathways essential for life. This pursuit allows graduate and undergraduate students to acquire specialized training in sugar and protein chemistry, as well as cell biology. This project is also integrated into an outreach program adaptable for K-12 students to learn about the building blocks of life.<br/><br/>Mucin glycoproteins are crucial for life but challenging to study due to their inherent chemical heterogeneity. These rigid proteins span the cell membrane and perform complex biological functions on both the extracellular and cytosolic sides of the bilayer. During this project, the PI will employ chemoenzymatic techniques to synthesize a series of chemically and mechanically tunable mucin glycodomains. These synthetic mucins will be used to engineer the glycocalyx of live cells by attaching the synthetic glycodomains to their surfaces through a combination of genetic engineering and chemical conjugation. This approach seeks to enable a systematic investigation of mucin glycocalyx-mediated cellular signaling functions both intra- and extracellularly. The PI will utilize their glycocalyx model to explore how glycan-mediated clustering initiates biochemical signaling and the role of mucins in regulating cell extrusion events that maintain epithelial homeostasis. The ultimate objective of this research is to develop tools for studying the glycocalyx and to contribute to the understanding of its fundamental biochemical and biophysical roles.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/19/2024
|
08/19/2024
|
None
|
Grant
|
47.049
|
1
|
4900
|
4900
|
2431001
|
{'FirstName': 'Jessica', 'LastName': 'Kramer', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jessica Kramer', 'EmailAddress': '[email protected]', 'NSF_ID': '000761899', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Utah', 'CityName': 'SALT LAKE CITY', 'ZipCode': '841129049', 'PhoneNumber': '8015816903', 'StreetAddress': '201 PRESIDENTS CIR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Utah', 'StateCode': 'UT', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'UT01', 'ORG_UEI_NUM': 'LL8GLEVH6MG3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF UTAH', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Utah', 'CityName': 'SALT LAKE CITY', 'StateCode': 'UT', 'ZipCode': '841129049', 'StreetAddress': '201 PRESIDENTS CIR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Utah', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'UT01'}
|
{'Code': '688300', 'Text': 'Chemistry of Life Processes'}
|
2024~543251
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431001.xml'}
|
Collaborative Research: ENG-BIOTECH: Mechanism-Guided Engineering of Thermophilic CRISPR-Cas13 for Ultrasensitive and Robust RNA Detection
|
NSF
|
11/01/2024
|
10/31/2027
| 199,997 | 199,997 |
{'Value': 'Standard Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Aleksandr Simonian', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922191'}
|
Infectious diseases are a major global health concern. Rapid and accurate detection of the presence of disease-causing RNA is crucial for effective diagnosis and control of these diseases. The CRISPR-Cas13 system is a cutting-edge technology for RNA detection. However, the currently used Cas13 enzymes can become unstable and lose their effectiveness during long-term storage and in field applications. This project aims to improve the stability and sensitivity of a heat-resistant version of the Cas13 enzyme, making it more reliable and sensitive for detecting RNA. This includes enhancing the enzyme's ability to recognize and cut RNA and combine it with advanced electrochemical devices to create a highly sensitive and stable detection method. The proposed scientific advancements are closely connected to educational outreach activities. The project will involve high school and community college students, particularly from underrepresented backgrounds, in biological and bioengineering research. Students will receive training in experimental techniques, data analysis, and scientific writing. Additionally, high school students will be introduced to CRISPR technology through a biotech academy and integrate the research findings into university courses. <br/><br/>The goal of the project is to combine mechanism-based protein engineering and cutting edge electrochemical devices to generate next-generation RNA detection tools for infectious disease diagnosis. The project will leverage the CRISPR-Cas13 system, which has shown great promise as next-generation diagnostics for in vitro RNA detection owing to its high specificity, programmability, and fast reaction rate. The collaborative project aims to first investigate the structure and mechanism of the recently discovered thermostable Cas13. Leveraging the mechanistic understanding, rational engineering of the thermostable Cas13 will be performed to produce new variants with superior thermostability and protease resistance, as well as enhanced target sensitivity and reaction speed. The engineered Cas13 variants will be combined with innovative electrochemical devices to enable ultrasensitive and robust RNA detection of various pathogens derived from clinical samples. Successful completion will provide superior RNA detection tools for medical and research applications, alongside novel insights into the Cas13 nuclease mechanism.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/15/2024
|
08/15/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2431018
|
{'FirstName': 'Yang', 'LastName': 'Gao', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yang Gao', 'EmailAddress': '[email protected]', 'NSF_ID': '000861956', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'William Marsh Rice University', 'CityName': 'Houston', 'ZipCode': '770051827', 'PhoneNumber': '7133484820', 'StreetAddress': '6100 MAIN ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'TX09', 'ORG_UEI_NUM': 'K51LECU1G8N3', 'ORG_LGL_BUS_NAME': 'WILLIAM MARSH RICE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'William Marsh Rice University', 'CityName': 'Houston', 'StateCode': 'TX', 'ZipCode': '770051827', 'StreetAddress': '6100 MAIN ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'TX09'}
|
{'Code': '164200', 'Text': 'Special Initiatives'}
|
2024~199997
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431018.xml'}
|
Collaborative Research: ENG-BIOTECH: Mechanism-Guided Engineering of Thermophilic CRISPR-Cas13 for Ultrasensitive and Robust RNA Detection
|
NSF
|
11/01/2024
|
10/31/2027
| 199,999 | 199,999 |
{'Value': 'Standard Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Aleksandr Simonian', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922191'}
|
Infectious diseases are a major global health concern. Rapid and accurate detection of the presence of disease-causing RNA is crucial for effective diagnosis and control of these diseases. The CRISPR-Cas13 system is a cutting-edge technology for RNA detection. However, the currently used Cas13 enzymes can become unstable and lose their effectiveness during long-term storage and in field applications. This project aims to improve the stability and sensitivity of a heat-resistant version of the Cas13 enzyme, making it more reliable and sensitive for detecting RNA. This includes enhancing the enzyme's ability to recognize and cut RNA and combine it with advanced electrochemical devices to create a highly sensitive and stable detection method. The proposed scientific advancements are closely connected to educational outreach activities. The project will involve high school and community college students, particularly from underrepresented backgrounds, in biological and bioengineering research. Students will receive training in experimental techniques, data analysis, and scientific writing. Additionally, high school students will be introduced to CRISPR technology through a biotech academy and integrate the research findings into university courses. <br/><br/>The goal of the project is to combine mechanism-based protein engineering and cutting edge electrochemical devices to generate next-generation RNA detection tools for infectious disease diagnosis. The project will leverage the CRISPR-Cas13 system, which has shown great promise as next-generation diagnostics for in vitro RNA detection owing to its high specificity, programmability, and fast reaction rate. The collaborative project aims to first investigate the structure and mechanism of the recently discovered thermostable Cas13. Leveraging the mechanistic understanding, rational engineering of the thermostable Cas13 will be performed to produce new variants with superior thermostability and protease resistance, as well as enhanced target sensitivity and reaction speed. The engineered Cas13 variants will be combined with innovative electrochemical devices to enable ultrasensitive and robust RNA detection of various pathogens derived from clinical samples. Successful completion will provide superior RNA detection tools for medical and research applications, alongside novel insights into the Cas13 nuclease mechanism.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/15/2024
|
08/15/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2431019
|
{'FirstName': 'Xue', 'LastName': 'Gao', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xue Gao', 'EmailAddress': '[email protected]', 'NSF_ID': '000824739', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Pennsylvania', 'CityName': 'PHILADELPHIA', 'ZipCode': '191046205', 'PhoneNumber': '2158987293', 'StreetAddress': '3451 WALNUT ST STE 440A', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'PA03', 'ORG_UEI_NUM': 'GM1XX56LEP58', 'ORG_LGL_BUS_NAME': 'TRUSTEES OF THE UNIVERSITY OF PENNSYLVANIA, THE', 'ORG_PRNT_UEI_NUM': 'GM1XX56LEP58'}
|
{'Name': 'University of Pennsylvania', 'CityName': 'PHILADELPHIA', 'StateCode': 'PA', 'ZipCode': '191046315', 'StreetAddress': '3701 Filbert Street', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'PA03'}
|
{'Code': '164200', 'Text': 'Special Initiatives'}
|
2024~199999
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431019.xml'}
|
Collaborative Research: ENG-BIOTECH: Mechanism-Guided Engineering of Thermophilic CRISPR-Cas13 for Ultrasensitive and Robust RNA Detection
|
NSF
|
11/01/2024
|
10/31/2027
| 200,000 | 200,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Aleksandr Simonian', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922191'}
|
Infectious diseases are a major global health concern. Rapid and accurate detection of the presence of disease-causing RNA is crucial for effective diagnosis and control of these diseases. The CRISPR-Cas13 system is a cutting-edge technology for RNA detection. However, the currently used Cas13 enzymes can become unstable and lose their effectiveness during long-term storage and in field applications. This project aims to improve the stability and sensitivity of a heat-resistant version of the Cas13 enzyme, making it more reliable and sensitive for detecting RNA. This includes enhancing the enzyme's ability to recognize and cut RNA and combine it with advanced electrochemical devices to create a highly sensitive and stable detection method. The proposed scientific advancements are closely connected to educational outreach activities. The project will involve high school and community college students, particularly from underrepresented backgrounds, in biological and bioengineering research. Students will receive training in experimental techniques, data analysis, and scientific writing. Additionally, high school students will be introduced to CRISPR technology through a biotech academy and integrate the research findings into university courses. <br/><br/>The goal of the project is to combine mechanism-based protein engineering and cutting edge electrochemical devices to generate next-generation RNA detection tools for infectious disease diagnosis. The project will leverage the CRISPR-Cas13 system, which has shown great promise as next-generation diagnostics for in vitro RNA detection owing to its high specificity, programmability, and fast reaction rate. The collaborative project aims to first investigate the structure and mechanism of the recently discovered thermostable Cas13. Leveraging the mechanistic understanding, rational engineering of the thermostable Cas13 will be performed to produce new variants with superior thermostability and protease resistance, as well as enhanced target sensitivity and reaction speed. The engineered Cas13 variants will be combined with innovative electrochemical devices to enable ultrasensitive and robust RNA detection of various pathogens derived from clinical samples. Successful completion will provide superior RNA detection tools for medical and research applications, alongside novel insights into the Cas13 nuclease mechanism.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/15/2024
|
08/15/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2431020
|
{'FirstName': 'Yi', 'LastName': 'Zhang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yi Zhang', 'EmailAddress': '[email protected]', 'NSF_ID': '000795640', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Connecticut', 'CityName': 'STORRS', 'ZipCode': '062699018', 'PhoneNumber': '8604863622', 'StreetAddress': '438 WHITNEY RD EXTENSION UNIT 11', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Connecticut', 'StateCode': 'CT', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'CT02', 'ORG_UEI_NUM': 'WNTPS995QBM7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CONNECTICUT', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Connecticut', 'CityName': 'STORRS', 'StateCode': 'CT', 'ZipCode': '062699018', 'StreetAddress': '438 WHITNEY RD EXTENSION UNIT 1133', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Connecticut', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'CT02'}
|
{'Code': '164200', 'Text': 'Special Initiatives'}
|
2024~200000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431020.xml'}
|
CIVIC-PG Track A: Community-driven Evaluation and Adoption of Innovative Approaches and Technologies to Enhance Wildfire Resilience on Maui
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Daan Liang', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922441'}
|
This Civic Innovation Challenge Planning Grant (CIVIC-PG) supports research on integrating scientific and traditional local knowledge, data, skills, and strategies to enhance community resilience to natural hazards, specifically wildfires. In August 2023, the Hawaiʻi Wildfires (also known as the Maui Wildfires) caused more than 100 deaths and damaged or destroyed around 3,000 buildings, leading to the deadliest wildfire in the U.S. in more than a century. The fires inflicted the most significant damage on the historic town of Lāhainā, and to a lesser extent in Upper Kula. Residents of Hawaiʻi, especially those on Maui, believe that the wildfires have provided a unique opportunity to learn important lessons and strengthen the resilience of local communities. Close collaboration between communities, local authorities, and researchers is critical to creating sustainable solutions for coping with climate and environmental instabilities and mitigating the impact of future wildfires. The on-site activities undertaken by this project promote community-level stewardship of lands through clearance and restoration. It also enables local families, communities, and agencies to improve their capacity to detect, prepare for, respond to and recover from wildfires. Moreover, this pilot project enhances the university’s partnership with underserved communities and non-profit organizations across Hawaiʻi to augment research, training, and communication. The outcomes of this project benefit a diverse group of stakeholders, including community planners, government agencies, land developers, and residents in fire-prone areas. <br/><br/>By forming a partnership between the university, local communities, and government agencies, this project seeks to build capacity and collaboratively design a model for local land stewardship. It strengthens ecological, social, cultural, and technological resilience to the increasing wildfire risk through: 1) collaboration with community members to integrate diverse approaches, data, and knowledge of land cover/land use changes to improve local-level land management; 2) community education and outreach to organize classes and workshops and deliver informational materials to citizens; 3) piloting fuel reduction and native species restoration; 4) technology integration and communication to rapidly detect wildfires and improve interconnection among community members; and 5) collaboration with local government agencies to design invasive species management plans, develop early warning systems, and improve post-fire recovery efforts. <br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/17/2024
|
07/17/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2431050
|
[{'FirstName': 'Sayed', 'LastName': 'Bateni', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sayed Bateni', 'EmailAddress': '[email protected]', 'NSF_ID': '000670869', 'StartDate': '07/17/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Clay', 'LastName': 'Trauernicht', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Clay Trauernicht', 'EmailAddress': '[email protected]', 'NSF_ID': '000791378', 'StartDate': '07/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Christopher', 'LastName': 'Shuler', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christopher K Shuler', 'EmailAddress': '[email protected]', 'NSF_ID': '000952830', 'StartDate': '07/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Sara', 'LastName': 'Tekula', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sara Tekula', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A06GH', 'StartDate': '07/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Hawaii', 'CityName': 'HONOLULU', 'ZipCode': '968222247', 'PhoneNumber': '8089567800', 'StreetAddress': '2425 CAMPUS RD SINCLAIR RM 1', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Hawaii', 'StateCode': 'HI', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'HI01', 'ORG_UEI_NUM': 'NSCKLFSSABF2', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF HAWAII', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Hawaii', 'CityName': 'HONOLULU', 'StateCode': 'HI', 'ZipCode': '968222382', 'StreetAddress': '2540 Dole Street', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Hawaii', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'HI01'}
|
[{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}, {'Code': '138500', 'Text': 'SSA-Special Studies & Analysis'}]
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431050.xml'}
|
CIVIC-PG Track A: A Multi-dimensional Approach to Transform Tribal Community Resilience Against Extreme Wind Hazards
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Daan Liang', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922441'}
|
The objective of this Civic Innovation Challenge Planning Grant (CIVIC-PG) is to support research on mitigating extreme wind hazards in Midwest tribal communities by co-developing, co-implementing, and validating a scalable socio-technical framework and a web-based computational platform to predict and assess risk and resilience. Resilience building within tribal communities has historically met many challenges, including limited technology access, integration, and implementation, lack of skillful workforce, and restricted access to tribal lands. Recent devastating events underscore an urgent need to enhance preparedness and infrastructure planning, particularly for tribes without federal recognition. Among them, extreme wind hazards in the Midwest are most threatening, causing service disruptions, economic instability, and potential loss of life. The computational platform is designed to facilitate information exchange, update preparedness frameworks, map hazard areas, and provide real-time evacuation and resource allocation. Training of local representatives improves data utilization and coverage, thus strengthening community resilience against natural hazards.<br/><br/>The project employs a multi-dimensional approach to 1) discover community vulnerabilities and interactions between technology, environment, infrastructures, and people, (2) create integrated analytical methods and resilience models for tribal communities, and (3) co-develop a web-based computational platform integrating resilience modeling, geographic information system, deep learning, and remote sensing. It brings together diverse expertise and partnerships to transform research and technology into practical solutions to enhancing resilience, promoting technology use, and supporting tribal self-reliance and decision-making. The project contributes to the advancement in interdisciplinary collaboration across resilience modeling, data analysis, geospatial science, and emergency management. The technology and framework are scalable for wider adoption.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/10/2024
|
07/10/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2431053
|
[{'FirstName': 'Yu-Che', 'LastName': 'Chen', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yu-Che Chen', 'EmailAddress': '[email protected]', 'NSF_ID': '000769679', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Chenyu', 'LastName': 'Huang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Chenyu Huang', 'EmailAddress': '[email protected]', 'NSF_ID': '000793793', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Xin', 'LastName': 'Zhong', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xin Zhong', 'EmailAddress': '[email protected]', 'NSF_ID': '000802679', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Edouardo', 'LastName': 'Zendejas', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Edouardo Zendejas', 'EmailAddress': '[email protected]', 'NSF_ID': '000919656', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Milad', 'LastName': 'Roohi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Milad Roohi', 'EmailAddress': '[email protected]', 'NSF_ID': '000940515', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Nebraska at Omaha', 'CityName': 'OMAHA', 'ZipCode': '681820001', 'PhoneNumber': '4025542286', 'StreetAddress': '6001 DODGE ST EAB 209', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Nebraska', 'StateCode': 'NE', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'NE02', 'ORG_UEI_NUM': 'FZRNFQTKADH1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF NEBRASKA', 'ORG_PRNT_UEI_NUM': 'FZRNFQTKADH1'}
|
{'Name': 'University of Nebraska at Omaha', 'CityName': 'OMAHA', 'StateCode': 'NE', 'ZipCode': '681820001', 'StreetAddress': '6001 DODGE ST EAB 209', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Nebraska', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'NE02'}
|
[{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}, {'Code': '138500', 'Text': 'SSA-Special Studies & Analysis'}]
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431053.xml'}
|
NLI: Research: Influence of Sustainability-Focused Course Interventions on Students' Engineering Identity Development
|
NSF
|
09/15/2024
|
08/31/2027
| 349,893 | 349,893 |
{'Value': 'Standard Grant'}
|
{'Code': '07050000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'EEC', 'LongName': 'Div Of Engineering Education and Centers'}}
|
{'SignBlockName': 'Matthew A. Verleger', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922961'}
|
Sustainability is an urgent and critical need that modern engineering must address. To this end, engineering students should develop a sustainability-focused outlook. This project will contribute to the goals of the NSF Research in the Formation of Engineers Program by integrating sustainability principles into engineering courses to cultivate a generation of engineers who are mindful of their roles and equipped to fulfill their responsibilities in fostering a sustainable future. Through the development of innovative course interventions guided by the Engineering for One Planet (EOP) Framework, this project will enhance students' understanding of sustainability across social, environmental, and economic dimensions, leading to the development of a sustainability-conscious engineering identity. By focusing on sustainability-conscious engineering identities, the project will not only prepare students to incorporate sustainability practices into professional engineering work but also promote diversity, equity, inclusion, and justice (DEIJ) within the engineering industry. The significance of this project lies in its potential to transform engineering curricula and pedagogy, and prepare graduates who are ready to contribute to a sustainable and equitable society.<br/><br/>This project will investigate how sustainability-focused course interventions help students develop a sustainability-conscious engineering identity. This will be explored in terms of students’ knowledge, attitudes, and behaviors across the social, environmental, and economic dimensions of sustainability. To achieve this goal, the project will be conducted in two phases. In the first phase, the research team will collaborate with faculty, departments, and other stakeholders to design and implement course interventions using the EOP framework. Approximately ten courses from the Rochester Institute of Technology’s (RIT) College of Engineering Technology and College of Engineering will be included in the study. The research will employ a multiple-case study design with each course serving as a case. The nature of the intervention in each course, ranging from single modules to full-term projects, will vary according to the course level, student’s background knowledge, and recommendations from the department and college curriculum committees. The second phase will involve collecting and analyzing data to explore the influence of these course interventions on students' engineering identity development using the analytical framework of Sustainability Consciousness. The research will utilize written reflections and in-person semi-structured interviews to gather qualitative data. Participants will include students enrolled in the courses in which interventions are implemented. Data will be collected from each course over a period of three years. Incremental changes will be made to the interventions based on student reflections and interviews, and course assessment data. Student reflections and interviews will be analyzed using thematic and process coding to identify shifts in students' knowledge, attitudes, and behaviors in the social, environmental, and economic dimensions of sustainability. This project will be guided by an advisory board comprising experts in STEM education, curriculum design, community engagement, EOP implementation, and DEIJ, to ensure its rigor and relevance. Expected outcomes include insights into the mechanisms underlying students’ identity development in terms of the role of engineers in sustainable development (knowledge), viewpoints toward addressing sustainability issues (attitude), and engagement in actions to actualize sustainability-related changes (behavior). These insights will inform the design of future curricular interventions within the cases under study and beyond. In addition, effective pedagogical strategies for integrating sustainability into engineering education and the development of transferable course materials will benefit the engineering education community and subsequently contribute to developing an engineering workforce aware of and equipped to address the sustainability needs of the modern world.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/02/2024
|
08/02/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2431057
|
[{'FirstName': 'Amanda', 'LastName': 'Bao', 'PI_MID_INIT': 'Y', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Amanda Y Bao', 'EmailAddress': '[email protected]', 'NSF_ID': '000591678', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Yewande', 'LastName': 'Abraham', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yewande S Abraham', 'EmailAddress': '[email protected]', 'NSF_ID': '000835929', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Lisa', 'LastName': 'Greenwood', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lisa L Greenwood', 'EmailAddress': '[email protected]', 'NSF_ID': '000887604', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Lucio', 'LastName': 'Salles de Salles', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lucio Salles de Salles', 'EmailAddress': '[email protected]', 'NSF_ID': '000919852', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ashish', 'LastName': 'Agrawal', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ashish Agrawal', 'EmailAddress': '[email protected]', 'NSF_ID': '000991730', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Rochester Institute of Tech', 'CityName': 'ROCHESTER', 'ZipCode': '146235603', 'PhoneNumber': '5854757987', 'StreetAddress': '1 LOMB MEMORIAL DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'NY25', 'ORG_UEI_NUM': 'J6TWTRKC1X14', 'ORG_LGL_BUS_NAME': 'ROCHESTER INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Rochester Institute of Tech', 'CityName': 'ROCHESTER', 'StateCode': 'NY', 'ZipCode': '146235603', 'StreetAddress': '1 LOMB MEMORIAL DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_PERF': 'NY25'}
|
{'Code': '134000', 'Text': 'EngEd-Engineering Education'}
|
2024~349893
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431057.xml'}
|
CISE MSI: RPP: IIS: Deep Clustering of Unlabeled Tabular Data for Transfer Learning in Heterogeneous Feature Space
|
NSF
|
01/01/2025
|
12/31/2026
| 200,000 | 200,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Michelle Rogers', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032920000'}
|
The recent artificial intelligence (AI) revolution has been possible due to the availability of large pre-trained image and language models, which are fine-tuned for various domain applications through knowledge transfer. Such cross-domain transfer learning is feasible because image patterns or text semantics are shared across many domains. In contrast, many business, medical, and scientific data sets are structured in rows and columns as tabular data, which surprisingly remain a challenge for modern AI due to heterogeneity in columns and tables. This project will investigate theoretical and analytical solutions to enable cross-domain transfer learning of tabular data by complementing theoretical statistics and AI expertise. A cross-domain learning framework will enable the aggregation of knowledge from heterogeneous tabular data sources. By leveraging state-of-the-art data clustering methods, this project will provide new computational frameworks to learn from untapped and unlabeled tabular data sources to advance data-driven health science and informatics. The project will also pave the path for foundation and collaboration in data science education and research to train future data scientists from historically underrepresented groups. <br/><br/>The project aims to investigate two unmet problems in tabular data science. First problem is hybrid deep representation clustering of unlabeled tabular data. Representation learning from unlabeled data is non-trivial, but highly practical when data samples in tables are hard to label by visually reading a heterogeneous feature space. This project will investigate deep clustering solutions for unlabeled tabular data by integrating multivariate statistical theories into innovative deep representation learning. The second problem is transfer knowledge across unlabeled data tables. Cross-domain and transfer learning approaches are one of the cornerstones of modern AI applied to image and text data. However, similar approaches are challenging in tabular data due to the heterogeneity in feature space and application domains. The project will leverage recent breakthroughs in modeling data distributions and statistics to learn a novel cluster-friendly deep feature space from unlabeled tabular data. The cluster-friendly representation will facilitate subsequent learning and distillation of mutual and complementary information between data tables to enable transfer learning. The computational frameworks will be evaluated on tabular data sets from real-world Electronic Health Records in patient risk stratification tasks. The project will share new algorithms with source code, exchange knowledge and publications to strengthen collaboration, and train students. All these project activities are imperative for establishing full-scale tabular data science research.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2431058
|
[{'FirstName': 'Manar', 'LastName': 'Samad', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Manar Samad', 'EmailAddress': '[email protected]', 'NSF_ID': '000788588', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Liang', 'LastName': 'Hong', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Liang Hong', 'EmailAddress': '[email protected]', 'NSF_ID': '000345898', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Norou', 'LastName': 'Diawara', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Norou Diawara', 'EmailAddress': '[email protected]', 'NSF_ID': '000352662', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Tennessee State University', 'CityName': 'NASHVILLE', 'ZipCode': '372091561', 'PhoneNumber': '6159637631', 'StreetAddress': '3500 JOHN A MERRITT BLVD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Tennessee', 'StateCode': 'TN', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'TN05', 'ORG_UEI_NUM': 'N63ZMY7UETA3', 'ORG_LGL_BUS_NAME': 'TENNESSEE STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Tennessee State University', 'CityName': 'NASHVILLE', 'StateCode': 'TN', 'ZipCode': '372091500', 'StreetAddress': '3500 JOHN A MERRITT BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Tennessee', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'TN05'}
|
{'Code': '173Y00', 'Text': 'CISE MSI Research Expansion'}
|
2024~200000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431058.xml'}
|
Cosmic Collisions, Relativistic Blasts, and their Remnants in the Era of Multi-Messenger Astronomy
|
NSF
|
06/01/2024
|
08/31/2026
| 431,250 | 431,250 |
{'Value': 'Standard Grant'}
|
{'Code': '03020000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'AST', 'LongName': 'Division Of Astronomical Sciences'}}
|
{'SignBlockName': 'Gioia Rau', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928729'}
|
GW170817 is the name given by astronomers to the merger of two neutron stars witnessed through its gravitational wave siren, an associated gamma-ray burst, and its glow at all wavelengths of light. This discovery marked the beginning of a golden age in time-domain multi-messenger astronomy. A research team at Texas Tech University will use radio observations to study the physics of multi-messenger transients. While this group helps shape the path forward for multi-messenger astronomy, it will also undertake educational and outreach initiatives aimed at building the next generation of scientists. These will include training students in computing and data analysis through the Radio Astronomy Data Imaging and Analysis Lab (RADIAL), a partnership between the National Radio Astronomy Observatory and fourteen minority-serving institutions of higher education and sponsoring the yearly public Bucy Distinguished Lecture to further encourage participation of the general public and local minorities in STEM. <br/><br/>This project has three main goals: (i) Conducting radio follow-up observations of neutron star - neutron star and neutron star - black hole systems discovered by ground-based gravitational wave detectors to constrain the physics of their ejecta and the nature of their remnants; (ii) Shedding light on the the similarities and differences between two types of stellar explosions: gamma-ray bursts and stripped-envelope core-collapse supernovae; (iii) Exploring future multi-messenger observing scenarios with the next generation Very Large Array radio telescope and ground-based gravitational-wave detectors. Mergers of neutron stars in binary systems observed through multiple messengers offer a unique opportunity to answer key open questions in a variety of fields, including gravitational and nuclear physics, relativistic astrophysics, and cosmology. Studying how neutron stars and black holes form and evolve, when isolated or paired in binaries, can shed light on the yet-to-be-understood diverse paths that bring massive stars toward their violent deaths, enriching the universe with its heaviest elements. Characterizing the properties of powerful blasts and ejecta from binary neutron star mergers and massive star collapses can give us invaluable information on particle acceleration mechanisms, magnetic field amplification, and the nature of the central engines powering the most relativistic cosmic jets. Unveiling the remnants of binary neutron star coalescences can constrain the equation of state of nuclear matter, providing a fundamental physics test. This award advances the goals of the Windows on the Universe Big Idea.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
05/13/2024
|
05/13/2024
|
None
|
Grant
|
47.049
|
1
|
4900
|
4900
|
2431072
|
{'FirstName': 'Alessandra', 'LastName': 'Corsi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Alessandra Corsi', 'EmailAddress': '[email protected]', 'NSF_ID': '000628946', 'StartDate': '05/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Johns Hopkins University', 'CityName': 'BALTIMORE', 'ZipCode': '212182608', 'PhoneNumber': '4439971898', 'StreetAddress': '3400 N CHARLES ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MD07', 'ORG_UEI_NUM': 'FTMTDMBR29C7', 'ORG_LGL_BUS_NAME': 'THE JOHNS HOPKINS UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Johns Hopkins University', 'CityName': 'BALTIMORE', 'StateCode': 'MD', 'ZipCode': '212182608', 'StreetAddress': '3400 N CHARLES ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MD07'}
|
[{'Code': '107Y00', 'Text': 'WoU-Windows on the Universe: T'}, {'Code': '121500', 'Text': 'STELLAR ASTRONOMY & ASTROPHYSC'}]
|
2023~431250
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431072.xml'}
|
SCC-CIVIC-PG Track A: BioEnergy and Fertilizer Production from Food Waste Enabled by Community Partnerships and Anaerobic Biotechnologies
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Christopher Balakrishnan', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922331'}
|
Green Era Educational NFP (Green Era) and the University of Michigan are working together in partnership to transform the landscape of waste management by fostering community resilience and social equity through the innovative use of bioenergy solutions. Green Era has developed a 9-acre vacant brownfield lot in the South Side of Chicago into a vibrant campus, hosting a renewable energy biodigester facility that uses food waste for operation and hub for urban agriculture and green jobs. Together, we envision a Research-Centered Pilot Project that will focus on optimizing their technological processes, engaging with their local communities, and developing educational materials to strengthen and amplify their positive community impact now and in the future. The work proposed will take a community-centric approach and contribute to broader positive impacts in the local community and beyond, such as increased economic opportunities, offset carbon, and support for healthier lifestyles. The outcomes of this work can be used to empower other communities and support economic and environmental prosperity, as well as community resilience. <br/><br/>In the planning scope of this project, we are motivated by the following research questions: 1) How might we characterize food waste streams and design an optimal blend of food waste sources as the substrate for biodigestion operation for Green Era? and 2) What are community priorities related to Green Era’s bioenergy operations and how do their priorities align or conflict with Green Era’s current processes? To answer these questions, we plan to run two workshops at Green Era’s campus to conduct technical analysis and community mapping to gather information and deepen our collective understanding. This information gathering will include community consultations, which will include semi-structured interviews with identified community partners, and technical feasibility studies, which will include laboratory characterizations of food waste and process optimization trials. Ultimately, the goal of the planning phase is to co-develop a strategic plan for Green Era based on our sociotechnical learnings that will be implemented in the project's next phase.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2431089
|
[{'FirstName': 'Lutgarde Maria', 'LastName': 'Raskin', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lutgarde Maria Raskin', 'EmailAddress': '[email protected]', 'NSF_ID': '000315733', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Sita', 'LastName': 'Syal', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sita M Syal', 'EmailAddress': '[email protected]', 'NSF_ID': '000928866', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'ZipCode': '481091079', 'PhoneNumber': '7347636438', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'MI06', 'ORG_UEI_NUM': 'GNJ7BBP73WE9', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MICHIGAN', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'StateCode': 'MI', 'ZipCode': '481091079', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'MI06'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431089.xml'}
|
Collaborative Research: CNS Core: Medium: FROOT: Future-Proof, Trustworthy Telemetry on Heterogeneous Networks
|
NSF
|
10/01/2023
|
11/30/2024
| 500,000 | 475,178 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Ann Von Lehmen', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924756'}
|
With the growth of the Internet and its importance in supporting the US economy, business, health, education and other services, it is critical to ensure both high performance and high availability of the networks underlying it. Increasingly, such networks include a heterogeneous set of network switches and other devices which must be monitored and controlled in a coordinated manner. Emerging networked applications, such as cloud gaming or cloud streamed augmented reality, are expected to further stress both control systems and network monitoring by requiring real-time response to rapid changes in traffic workloads. This project aims to address the needs of future network control by enabling a network telemetry infrastructure that can provide timely, accurate, and trusted information about ongoing activities in the network<br/><br/><br/>This project proposes FROOT, a future-proof, trustworthy telemetry infrastructure for networks of heterogeneous programmable devices (e.g., programmable switch, SmartNIC, CPU, and DPU). The project takes an interdisciplinary approach spanning algorithms, systems, and security to inform the design and implementation of next generation telemetry systems through the following: (1) universal sketch-based algorithmic design and implementation for current and new measurement tasks and network devices; (2) novel network-wide resource optimization for handling network dynamics; and (3) trustworthy sketch deployment into heterogeneous devices to obtain critical telemetry information. The researchers also plan to deploy their network telemetry system at Mass Open Cloud testbed, an open public cloud project led by Boston University and other institutions in Massachusetts. The project will result in the development of open-source tools, algorithms, and prototype implementations that will reduce the time to deploy sketch-based telemetry in real-world scenarios.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
06/02/2024
|
06/02/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2431093
|
{'FirstName': 'Zaoxing', 'LastName': 'Liu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zaoxing Liu', 'EmailAddress': '[email protected]', 'NSF_ID': '000842004', 'StartDate': '06/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'ZipCode': '207425100', 'PhoneNumber': '3014056269', 'StreetAddress': '3112 LEE BUILDING', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MD04', 'ORG_UEI_NUM': 'NPU8ULVAAS23', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MARYLAND, COLLEGE PARK', 'ORG_PRNT_UEI_NUM': 'NPU8ULVAAS23'}
|
{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'StateCode': 'MD', 'ZipCode': '207425100', 'StreetAddress': '3112 LEE BUILDING', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'MD04'}
|
{'Code': '171400', 'Text': 'Special Projects - CNS'}
|
2021~475178
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431093.xml'}
|
CIVIC-PG Track B - Leveraging a connected network of unattended micro-pantries to reduce food waste and improve food security
|
NSF
|
10/01/2024
|
03/31/2025
| 74,999 | 74,999 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Vishal Sharma', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928950'}
|
Traditional Hunger Relief Organizations (HROs) play a central role in reducing food insecurity. However, they face increasing challenges in equitably distributing rescued food. Vulnerable populations, such as the elderly, physically disabled individuals, and households with children, are often not able to access HROs during limited opening hours. Moreover, HROs often do not rescue food from smaller businesses, such as cafes, restaurants, and households which contribute to 70 percent of food waste in urban areas. Instead, HROs rely mostly on larger supply chains, not directly reducing food waste at a neighbourhood level. This project proposes to pilot a decentralized network of connected, unattended food micro-pantries to provide real-time information on existing demand for rescued food to food donors, collect food donations at a micro-scale level across neighborhoods of the Seattle study area, and monitor food safety. Micro-pantries are an emerging community-driven concept of independent, small, unattended, open-access, and community-run food pantries and fridges that are hosted on public-right-of-way or private properties and maintained by community members and local organizations. The disaggregated network of micro-pantries could support HROs as additional, more accessible and resilient food sources available closer to vulnerable communities and support more localized food rescue from households and local businesses. <br/><br/>The research team will prototype a wireless sensor platform installed at selected micro-pantries to collect food donations and pick-up data and provide real-time information to community groups, HROs, and local businesses to optimize the distribution of rescued food. The project is the first empirical study to quantitatively analyze micro-pantries' role in fighting food insecurity and improving equitable access to healthy eating. The research team will (1) perform a geospatial analysis of the existing network of micro-pantries in Seattle, WA; (2) develop and test a novel low-cost sensing system to detect food donations and pick-ups and measure food conditions; (3) develop a food donation training protocol for households and businesses located in proximity to micro-pantries; (4) estimate empirical demand and supply models to distribute rescued food optimally; (5) perform community outreach to document current food waste and food rescue practices. This research will provide a valuable, first-of-its-kind formal study of micro-pantries as a potential solution to food security that seeks to close gaps in traditional food rescue distribution. The results will provide key data to scale up programs that benefit low-income, food-insecure individuals, establishing a proof of concept for new community-based food distribution methods. The team includes experts from the University of Washington on urban distribution systems, sensor systems, and food safety, as well as a community partner working with local HROs to support food rescue and distribution. <br/><br/>This project is in response to the Civic Innovation Challenge program’s Track B. Bridging the gap between essential resources and services & community needs and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/02/2024
|
08/02/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2431098
|
[{'FirstName': 'Anne', 'LastName': 'Goodchild', 'PI_MID_INIT': 'V', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Anne V Goodchild', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A06C0', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Giacomo', 'LastName': 'Dalla Chiara', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Giacomo Dalla Chiara', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A04CY', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'ZipCode': '981951016', 'PhoneNumber': '2065434043', 'StreetAddress': '4333 BROOKLYN AVE NE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Washington', 'StateCode': 'WA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'WA07', 'ORG_UEI_NUM': 'HD1WMN6945W6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WASHINGTON', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'StateCode': 'WA', 'ZipCode': '981951016', 'StreetAddress': '4333 BROOKLYN AVE NE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Washington', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'WA07'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~74999
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431098.xml'}
|
I-Corps: Translation potential of infrastructure-enabled safe autonomy
|
NSF
|
07/01/2024
|
06/30/2025
| 50,000 | 50,000 |
{'Value': 'Standard Grant'}
|
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
|
{'SignBlockName': 'Jaime A. Camelio', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922061'}
|
The broader impact of this I-Corps project is the development of a technology system for smart infrastructure enabled autonomy. The promise of autonomous vehicles (AVs) has not come true despite the tremendous economic and societal benefits of AVs, potentially avoiding 40,000+ fatalities annually. The complexity, unreliability, and cost of additional on-board sensors required for autonomous driving have been major roadblocks preventing significant market deployment and adoption. As a result, the only viable market for AVs has been ride sharing and hauling services. The poor performance of robo-taxis has increased safety concerns over these technologies. For instance, such AVs have blocked road and emergency vehicles. They have also been involved in hundreds of crashes, including fatal ones. A significant portion of the underlying technological challenges can be resolved by leveraging smart infrastructure, leveraging recent dramatic growth in connectivity – 4G-LTE/5G and edge computers. This project will help overcome the challenges associated with complex driving scenarios, such as interaction with emergency vehicles, detecting vulnerable road users, merging onto highways, picking up and dropping off customers, etc. <br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of an integrated hardware/software platform that leverages sensors on infrastructure to infer traffic conditions and create a common situational awareness for all entities on the road. The platform sends situational awareness information wirelessly to vehicles and other consumers for real-time use, in-turn enabling multiple benefits, such as lower cost and faster deployment of autonomous vehicles, improved vulnerable road user safety, traffic optimization, and road maintenance. For these applications to be effective, situational awareness needs to be generated in real-time and be reliable across a range of sensing and communication faults and environmental conditions (adverse conditions). The core algorithms and software implementations developed during research based on resilient data fusion, enable automatic detection, mitigation, and graceful recovery from adverse conditions.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
06/17/2024
|
06/17/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2431110
|
{'FirstName': 'Swaminathan', 'LastName': 'Gopalswamy', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Swaminathan Gopalswamy', 'EmailAddress': '[email protected]', 'NSF_ID': '000759611', 'StartDate': '06/17/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Texas A&M Engineering Experiment Station', 'CityName': 'COLLEGE STATION', 'ZipCode': '778433124', 'PhoneNumber': '9798626777', 'StreetAddress': '3124 TAMU', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'TX10', 'ORG_UEI_NUM': 'QD1MX6N5YTN4', 'ORG_LGL_BUS_NAME': 'TEXAS A&M ENGINEERING EXPERIMENT STATION', 'ORG_PRNT_UEI_NUM': 'QD1MX6N5YTN4'}
|
{'Name': 'Texas A&M Engineering Experiment Station', 'CityName': 'COLLEGE STATION', 'StateCode': 'TX', 'ZipCode': '778433123', 'StreetAddress': '3123 TAMU', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'TX10'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431110.xml'}
|
CIVIC-PG Track A Building a coalition of scientists, Tribal representatives, and resource managers to test forest management effects on summer low flows in the Pacific Northwest
|
NSF
|
10/01/2024
|
03/31/2025
| 73,406 | 73,406 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Christopher Balakrishnan', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922331'}
|
Summer streamflows are critically low in numerous Pacific Northwest watersheds and are projected to decline further as temperatures rise and snowpack diminishes. These flow conditions result in poor quality aquatic habitats that are detrimental to salmon and other fish. The Nooksack Tribe, along with other Tribes in the region, are looking closely at management options that could help to sustain the survival of salmon, which are critical for cultural, spiritual, environmental, and economic uses. Forests are a key influence on the amount and timing of streamflow in a watershed, and forest management approaches such as thinning in lieu of clearcut harvest may drive increased streamflow during the dry summer season. A few previous studies support this concept based on observational data collection and numerical modeling, but there is limited confidence in these effects for western Washington due to a lack of regionally relevant observations and modeling. This project will assemble a regional coalition of scientists, Tribal representatives, and resource managers to collect relevant data, implement modeling, and provide actionable results that can inform strategies, decisions, and policy. <br/><br/>In the Pacific Northwest region of the United States, threatened and endangered salmon species sustain continued losses due to low summer flows and elevated stream temperatures. These critical streams are fed by watersheds that have experienced over a century of clear-cut timber harvest rotations, which have resulted in a mosaic of young, regenerating forest stands. Preliminary investigations of the effect of forest age and regeneration on summer low flows indicate that the legacy of even-age management may have contributed to declines in summer flows relative to mature old growth stands, but the issue is still understudied. For example, model representations of forest transpiration as a function of stand age is based on two studies located in the coastal range of Oregon, rather than in upland forest plantations of the western Cascades. This project aims to build a community of Tribal representatives, scientists, and water managers to guide the development of a targeted, decision-relevant research plan. Stage 1 will include workshops, field reconnaissance, and instrumentation testing, and Stage 2 aims to collect sap flux, soil moisture, and snow data across forest types to support testing and implementation of two hydrological models. Together, the field and modeling approaches will build actionable knowledge of the hydrologic linkages between the upper watershed, where forest management is occurring, and the stream channel, where salmon are spawning and rearing. <br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/02/2024
|
08/02/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2431113
|
{'FirstName': 'Nicoleta', 'LastName': 'Cristea', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nicoleta C Cristea', 'EmailAddress': '[email protected]', 'NSF_ID': '000792362', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'ZipCode': '981951016', 'PhoneNumber': '2065434043', 'StreetAddress': '4333 BROOKLYN AVE NE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Washington', 'StateCode': 'WA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'WA07', 'ORG_UEI_NUM': 'HD1WMN6945W6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WASHINGTON', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'StateCode': 'WA', 'ZipCode': '981951016', 'StreetAddress': '4333 BROOKLYN AVE NE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Washington', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'WA07'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~73406
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431113.xml'}
|
Conference: International Phytobiomes 2024 - Harvesting the Future: Bridging Phytobiomes, Agriculture and Climate
|
NSF
|
07/15/2024
|
06/30/2025
| 17,970 | 17,970 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Aardra Kachroo', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927826'}
|
The International Phytobiomes Conference 2024 (Phytobiomes 2024) – Harvesting the Future: Bridging Phytobiomes, Agriculture and Climate is an international conference that brings together a broad community of U.S. and international researchers and scientists from the public and private sector to collectively advance the newly emerging field of phytobiomes research. <br/>A Phytobiome is a plant (phyto-) in a distinct geographical unit (-biome). Phytobiome research is a system-level approach focused on the complex interactions between plants, micro- and macro-organisms, soils, climate, environment, and management practices that affect the sustainable production of plants. Understanding the diverse and dynamic processes within phytobiomes is essential for ensuring the sustained health and productivity of crops, plant ecosystems, and, ultimately, consumers of plants and plant products. Phytobiomes 2024 will be held November 19-21, 2024 in St. Louis, Missouri, USA. This unique and multidisciplinary conference will advance the community’s knowledge of the diverse disciplines focusing on phytobiomes and build momentum to apply this knowledge in an integrative, collaborative way to increase the sustainable production of food, feed, and fiber while minimizing losses from pests, pathogens, and environmental stresses. <br/><br/>The International Phytobiomes Conference 2024 (Phytobiomes 2024) – Harvesting the Future: Bridging Phytobiomes, Agriculture and Climate will explore current and needed advances and opportunities for future research collaborations, thereby setting a stage to encourage the development of international and public-private collaborations to push this field forward. Additionally, basic and applied research priorities will be discussed to ensure that a strong science-based foundation is established to accelerate the translation to agricultural producers. Plant and soil microbiomes will be a major focus as these areas require the most advancements for translation. Conference speakers will include scientists and agricultural practitioners from diverse disciplines who are engaged in research, education, application, and outreach at various levels in the agricultural system. Educating growers about the latest scientific developments and scientists about growers’ needs will ensure ultimate utility of research investments in microbiomes and phytobiome systems. Conference discussions will help identify strategic research priorities, technology or resource needs. They will also facilitate the establishment of multidisciplinary research collaborations and partnerships. Expected outcomes include the development and distribution of white papers on topics such as soil health, controlled environment agriculture, regulatory science. Additionally, education and outreach activities will engage the scientific and agricultural communities and society at large. The conference will seek input from students and early career professionals and educate them on the opportunities within phytobiomes science and applications. Overall, the Phytobiomes 2024 Conference will result in a cohesive research community with a clear focus and deep understanding of complex plant systems, facilitating the identification of future collaborative research areas that can positively impact plant-based agriculture.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/11/2024
|
07/11/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2431115
|
{'FirstName': 'Dusti', 'LastName': 'Gallagher', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dusti D Gallagher', 'EmailAddress': '[email protected]', 'NSF_ID': '000843441', 'StartDate': '07/11/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'INTERNATIONAL ALLIANCE FOR PHYTOBIOMES RESEARCH, INC.', 'CityName': 'EAU CLAIRE', 'ZipCode': '547013024', 'PhoneNumber': '3012218636', 'StreetAddress': '4620 VILLAGE TERRACE CT', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Wisconsin', 'StateCode': 'WI', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'WI03', 'ORG_UEI_NUM': 'PVY1NATDE743', 'ORG_LGL_BUS_NAME': 'INTERNATIONAL ALLIANCE FOR PHYTOBIOMES RESEARCH, INC', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'INTERNATIONAL ALLIANCE FOR PHYTOBIOMES RESEARCH, INC.', 'CityName': 'EAU CLAIRE', 'StateCode': 'WI', 'ZipCode': '547013024', 'StreetAddress': '4620 VILLAGE TERRACE CT', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Wisconsin', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'WI03'}
|
[{'Code': '047Y00', 'Text': 'Plant-Biotic Interactions'}, {'Code': '132900', 'Text': 'Plant Genome Research Project'}]
|
2024~17970
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431115.xml'}
|
CIVIC-PG Track A: Sustainable Biochar to Mitigate Freshwater HABs: Building Climate Resilient Rural Communities
|
NSF
|
09/01/2024
|
03/31/2025
| 74,995 | 74,995 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Kirsten Schwarz', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922416'}
|
Lakes worldwide are impacted by harmful algal blooms (HABs), also known as cyanoHABs. HABs can lower water quality and produce toxins, impairing fisheries, recreational waters, and drinking water sources. HABs are often related to nutrient pollution, but nutrient reductions from surrounding watersheds require collaboration, awareness, and community buy-in to make sustainable long-term changes and prevent bloom formation. This is particularly the case for areas that have limited access to drinking water infrastructure and where the impacts of HABs have been largely overlooked. In this project, community-based activities engage two rural communities in Western Oregon near Tenmile Lakes and Dorena Lake with respect to HABs awareness, risks, and vulnerabilities. The communities’ economies are reliant on watershed resources, e.g., timber and agriculture, that may contribute to nutrient loading, and on resources provided by the impacted lake, such as fishing, drinking water, and irrigation water. In partnership with rural stakeholders, organizations, and community members, this project explores climate-smart, sustainable, value-added intervention strategies to prevent HABs and reduce health risks.<br/><br/>Collaborating with civic partners focused on environment and livelihood, our research addresses knowledge gaps regarding the health risks and economic impacts of cyanoHABs in rural regions. We work with local communities to address the loss of water security due to cyanoHABs and test the use of a carbon by-product technology, biochar, to mitigate impacts of cyanoHABs. Biochar is used in agriculture and forestry to improve soil and ecosystem health. Here we apply it in the context of watersheds and water treatment. Through roundtables, workshops, interviews, and pilot experiments, and in collaboration with civic partners, stakeholders, and impacted community members, our research assesses the efficacy, feasibility, and sustainability of local biochar (i) to enhance near shore buffer zones designed to mitigate nutrient loading and reduce frequency and severity of blooms and (ii) to remove cyanotoxins through gravity-fed filters. Our work informs mitigation and water treatment strategies in two rural communities and helps inform other projects in rural communities impacted by cyanoHABs globally.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2431141
|
{'FirstName': 'Amber', 'LastName': 'Roegner', 'PI_MID_INIT': 'F', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Amber F Roegner', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A06JD', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Loyola University of Chicago', 'CityName': 'CHICAGO', 'ZipCode': '606112147', 'PhoneNumber': '7735082471', 'StreetAddress': '820 N MICHIGAN AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'IL05', 'ORG_UEI_NUM': 'CVNBL4GDUKF3', 'ORG_LGL_BUS_NAME': 'LOYOLA UNIVERSITY OF CHICAGO', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Loyola University of Chicago', 'CityName': 'CHICAGO', 'StateCode': 'IL', 'ZipCode': '606112147', 'StreetAddress': '820 N MICHIGAN AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'IL05'}
|
{'Code': '727500', 'Text': 'Cross-BIO Activities'}
|
2024~74995
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431141.xml'}
|
Collaborative Research: The Massive and Distant Clusters of WISE Survey 2
|
NSF
|
08/01/2024
|
08/31/2024
| 101,571 | 14,541 |
{'Value': 'Standard Grant'}
|
{'Code': '03020000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'AST', 'LongName': 'Division Of Astronomical Sciences'}}
|
{'SignBlockName': 'ANDREAS BERLIND', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032925387'}
|
The team will search for galaxy clusters and protoclusters in the distant Universe, back to the time when the first clusters were forming, allowing for detailed studies of the most massive galaxies in the universe at the time when they were rapidly growing. The program is based upon catalogs created by NASA’s Wide-field Infrared Survey Explorer (WISE), a space-based observatory that performed an all-sky survey in the infrared. Combining the WISE data with catalogs from the Dark Energy Camera (DECam) on NSF’s Blanco telescope at Cerro Tololo Interamerican Observatory in Chile will allow the team to determine where the first clusters are forming in a 3D volume of the universe. The project also includes a joint virtual public viewing night program at both institutions using remote observing from the Rosemary Hill Observatory. This plan enables public engagement during the pandemic and will expand the reach of public observing programs in both states post-covid. <br/><br/>This project will detect and characterize the massive galaxy cluster population at 0.5<z<2 over 10,480 sq. degrees, building upon a previous cluster survey by the same team, which focused upon galaxy clusters at z~1. The resulting cluster sample will enable detailed investigations of the evolution of massive galaxies in the most overdense environments since the epoch of peak star formation and rapid mass assembly. By extending the redshift baseline to z = 2, the project will reach into the era of protoclusters, in which the first massive clusters are just forming and embedded in larger scale protocluster environments comprised of dense filaments and less massive groups that will be accreted by the central clusters at later times. A combination of DECam and WISE data will be used to compute Bayesian photometric redshift probability distributions for the WISE galaxy sample and then to detect cluster scale overdensities within a 3-dimensional data cube. The PIs will foster the career development of the students working on this project.. The team will initiate and run a joint virtual public night program at their institutions using remote observing from the Rosemary Hill Observatory. This plan enables public engagement during the pandemic and will expand the reach of public observing programs in both states post-covid.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/19/2024
|
07/19/2024
|
None
|
Grant
|
47.049
|
1
|
4900
|
4900
|
2431150
|
{'FirstName': 'Mark', 'LastName': 'Brodwin', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mark Brodwin', 'EmailAddress': '[email protected]', 'NSF_ID': '000682786', 'StartDate': '07/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Eureka Scientific Inc', 'CityName': 'OAKLAND', 'ZipCode': '946023017', 'PhoneNumber': '5103737939', 'StreetAddress': '2452 DELMER ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'CA12', 'ORG_UEI_NUM': 'FMPGW7JS2SK3', 'ORG_LGL_BUS_NAME': 'EUREKA SCIENTIFIC, INC.', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Eureka Scientific Inc', 'CityName': 'OAKLAND', 'StateCode': 'CA', 'ZipCode': '946023017', 'StreetAddress': '2452 DELMER ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'CA12'}
|
{'Code': '121700', 'Text': 'EXTRAGALACTIC ASTRON & COSMOLO'}
|
2021~14541
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431150.xml'}
|
Conference: BRIDGE: Building Research Initiatives and Developmental Growth for Excellence
|
NSF
|
09/01/2024
|
08/31/2025
| 53,400 | 53,400 |
{'Value': 'Standard Grant'}
|
{'Code': '11060000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'EES', 'LongName': 'Div. of Equity for Excellence in STEM'}}
|
{'SignBlockName': 'Sonja Montas-Hunter', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927404'}
|
With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI Program), the aim of the conference proposed by the University of Puerto Rico at Aguadilla will enhance research funding accessibility for faculty at institutions of higher education in Puerto Rico's western region. The initiative addresses challenges such as limited proposal writing experience, inadequate preparation resources, and lack of professional networks by organizing a comprehensive conference. This conference will provide training, facilitate workshops, and foster collaboration among researchers, thereby increasing federal research proposal submissions and contributing to a more equitable and inclusive research environment in Puerto Rico.<br/><br/>The project will pursue three primary objectives: (1) Inform professors, administrative staff, and faculty from universities, community, and technical colleges about National Science Foundation (NSF) funding mechanisms to encourage and increase their participation in research proposal submissions. (2) Conduct an interactive and educational workshop to provide participants with detailed knowledge of NSF Program Directors' roles and functions, best practices for preparing, submitting, and managing successful research proposals, including budget development and financial management, while promoting inclusion, equity, and diversity in research. (3) Promote collaboration and networking among researchers and NSF Program Directors through group work sessions, interactive discussions, and networking opportunities during the conference. Anticipated outcomes include enhanced research capacity, increased proposal submissions, and a more diverse and innovative scientific community in Puerto Rico. The HSI Program aims to enhance undergraduate STEM education and build capacity at HSIs. Projects supported by the HSI Program will also generate new knowledge on how to achieve these aims.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/12/2024
|
08/12/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2431153
|
[{'FirstName': 'Vanessa', 'LastName': 'Lopez-Quiles', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Vanessa Lopez-Quiles', 'EmailAddress': '[email protected]', 'NSF_ID': '000847844', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Miguel', 'LastName': 'Méndez-González', 'PI_MID_INIT': 'P', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Miguel P Méndez-González', 'EmailAddress': '[email protected]', 'NSF_ID': '000629253', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'University of Puerto Rico at Aguadilla', 'CityName': 'AGUADILLA', 'ZipCode': '006031309', 'PhoneNumber': '7878901265', 'StreetAddress': '252 CALLE BELT', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Puerto Rico', 'StateCode': 'PR', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'PR00', 'ORG_UEI_NUM': 'LY7FAJLUV9T9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF PUERTO RICO', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Puerto Rico at Aguadilla', 'CityName': 'AGUADILLA', 'StateCode': 'PR', 'ZipCode': '006031309', 'StreetAddress': '252 CALLE BELT', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Puerto Rico', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'PR00'}
|
{'Code': '077Y00', 'Text': 'HSI-Hispanic Serving Instituti'}
|
2024~53400
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431153.xml'}
|
CIVIC-PG Track A: Resilient Arctic Coastal Communities to Coastal Hazards
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}
|
{'SignBlockName': 'Barbara Ransom', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927792'}
|
Warming Arctic temperatures are causing permafrost regions of the far north latitudes to thaw for the first time in millennia. These regions make up a large portion of the world’s northern most coastlines. Permafrost consists of frozen sediments that, when temperatures rise like they are now, causes the ice inside them to melt. Ice-like minerals, called clathrates, that abound in permafrost also decompose and release additional water and methane. The combination of liquefaction of the sediment and corresponding decrease in sediment volume causes deflation resulting in ground instability, subsidence, and accelerated coastal erosion. Erosion along Arctic coasts threatens not only coastal communities, but also installed infrastructure like roads, harbors, airfields, pipelines, and other essential elements of modern civilization. This Civic Innovation Challenge (CIVIC) planning process brings together university scientists, Arctic indigenous people living on the coast in the North Slope of Alaska and their community organizations, North Slope harbor masters, and other North Slope interested parties to co-design hazard maps that can be used to identify areas in peril, those that will become so in the near future, and areas that would be protected from the impacts of coastal erosion. Such a map will provide a much needed high-resolution tool to help improve coastal Alaskan community resilience and inform their planning and possible relocation of people and infrastructure for the future in a rapidly warming Arctic. The planning team consists of scientists from Penn State and the Universities of Alaska Fairbanks and Alaska Southeast and the following Alaskan entities: IUC Sciences LLC which represents the community of Utqiagvik; the Port Authority of North Slope/Barrow; the Office of Risk Management in the Department of Administration of North Slope/Barrow; and indigenous members of the communities of Utqiagvik, Point Lay, Wainwright, and Kaktovik. All will be part of a 3-day CIVIC planning meeting workshop that will be held at Utqiagvik to define and co-design the map and its analytical tools and user-interface. The map will provide significantly higher resolution than those already available to North Slope communities. Broader impacts of the work include development of a tool that can help inform residents and infrastructure along the North Slope of Alaska about areas at high risk and vulnerability to climate change, improve planning; protection; and relocation of assets and homes to locations safe from flooding, coastal erosion, and subsidence. Impacts also include the training of North Slope residents and land use managers on use of the map and its tools to increase climate resilience of Arctic communities, many of which are inhabited by indigenous people. It will also engage indigenous youth, using the map and its discovery tools to promote interest in, and the mastery of, science and technology concepts. The project team will gain valuable experience working with Alaskan key stakeholders, and North Slope of Alaska communities will see how the transition of foundational research to practice can achieve long-term societal benefits. <br/><br/>This CIVIC project focuses on providing high resolution, interactive coastal hazard maps and other on-line tools to help Alaskan coastal communities improve their resilience to the impacts of climate change. More than 200 Alaska Native villages are presently suffering from coastal erosion and flooding; and thirty-one Alaskan villages currently face imminent threats of coastal inundation and need relocation. The goal of this Civic Innovation Challenge (CIVIC) planning period is to bring together key stakeholders from across the north Arctic coastal area to co-design, with the science team: elements; applications; the user interface; and data visualizations of a high-resolution, coastal, climate hazard map that would be developed and implemented in a follow-on CIVIC proposal. In the course of North Slope hazard map creation, the CIVIC team will use their experience with North Slope indigenous communities to determine the best way to engage far flung rural, low-technology, predominantly subsistence-oriented, Native Alaskan communities and deliver a tool that is useful to them and that they can use to increase their resilience to climate change. The project also establishes effective means and protocols for co-designing, with stakeholders, high-spatial-resolution Arctic coastal hazard maps that simultaneously include the three major types of Alaskan coastal hazards (i.e., coastal erosion, flooding, land subsidence). The project will also explore mechanisms that could provide sustainability and long-term integration of new data into the map. The team will use this experience to see whether the map can be used as a vehicle to determine real and long-lasting community benefits of science/community interactions. Partners in this CIVIC project include university faculty and regional and local governments, civic organizations, and Indigenous communities. Partners include Native Alaskan village corporations, the North slope Port Authority, and other North Slope stakeholders including North Slope village residents. To achieve the planning process goal, a multi-stakeholder meeting will be held in an Alaskan North Slope town to garner community-wide perspectives and work with them to co-design the high resolution hazard map and its attendant applications. This planning process will result in North Slope community access to high-resolution hazard information and technology and training, in its use, to accelerate the learning and technology implementation needed to build more climate-ready Arctic communities. This planning process will also improve the understanding of how community-based efforts can be designed to provide improved nature-based solutions to climate change and will foster and strengthen collaboration between researchers and community stakeholders, develop new collaborations and partnerships, refine the research vision to enable submission of a successful follow-on proposal that will implement the community vision, and provide information to address research questions and develop evaluation methods and measures for the follow-on project.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy. It was funded by the NSF Directorate for Geosciences and Directorate for Computer Information Science and Engineering.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/17/2024
|
08/17/2024
|
None
|
Grant
|
47.050, 47.070
|
1
|
4900
|
4900
|
2431163
|
[{'FirstName': 'Anne', 'LastName': 'Jensen', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Anne M Jensen', 'EmailAddress': '[email protected]', 'NSF_ID': '000172525', 'StartDate': '08/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ming', 'LastName': 'Xiao', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ming Xiao', 'EmailAddress': '[email protected]', 'NSF_ID': '000408156', 'StartDate': '08/17/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Dmitry', 'LastName': 'Nicolsky', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dmitry J Nicolsky', 'EmailAddress': '[email protected]', 'NSF_ID': '000546192', 'StartDate': '08/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Pennsylvania State Univ University Park', 'CityName': 'UNIVERSITY PARK', 'ZipCode': '168021503', 'PhoneNumber': '8148651372', 'StreetAddress': '201 OLD MAIN', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '15', 'CONGRESS_DISTRICT_ORG': 'PA15', 'ORG_UEI_NUM': 'NPM2J7MSCF61', 'ORG_LGL_BUS_NAME': 'THE PENNSYLVANIA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Pennsylvania State Univ University Park', 'CityName': 'UNIVERSITY PARK', 'StateCode': 'PA', 'ZipCode': '168021503', 'StreetAddress': '201 OLD MAIN', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '15', 'CONGRESS_DISTRICT_PERF': 'PA15'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431163.xml'}
|
CIVIC-PG Track B: Community-Driven, AI-Powered Thermal Imaging for Accessible Window Air Infiltration and Leakage Measurement
|
NSF
|
10/01/2024
|
03/31/2025
| 74,996 | 74,996 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'David Corman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928754'}
|
Many low-income households in the United States face high energy bills, with some spending up to 13% of their income on energy, compared to the national average of 2.9%. This disparity is often due to inefficient windows and poor insulation, especially in older homes built before the 1960s. These homes suffer from air leaks, drafts, and inconsistent indoor temperatures, leading to increased energy consumption and higher bills. Additionally, the residents' health is adversely affected during extreme weather conditions such as heatwaves and wildfires. Traditional methods to measure window air leakage, like the blower-door test, are expensive and disruptive, making them impractical for many low-income communities. Without documented leakage data, these communities miss out on retrofit grants meant to improve energy efficiency and climate resilience. This project aims to fill this gap by developing a cost-effective, community-driven method to accurately measure window air infiltration and leakage using drone-mounted infrared/thermal imaging combined with artificial intelligence (AI).<br/><br/>The project will co-develop an innovative approach for rapid data collection and analysis by focusing on overburdened communities. The objectives are to conduct stakeholder focus groups, coordinate future window replacements, and perform in-lab and field experiments to calibrate thermal imaging for air leakage detection. The project aims to empower these areas to access retrofit grants, enhance climate resilience, improve energy efficiency, and ultimately reduce energy costs and improve residents' health and safety. This initiative also addresses environmental injustice, ensuring that affordable and sustainable housing is accessible to those who need it most.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track B. Bridging the gap between essential resources and services & community needs and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/12/2024
|
08/12/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2431169
|
[{'FirstName': 'Lucio', 'LastName': 'Soibelman', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lucio Soibelman', 'EmailAddress': '[email protected]', 'NSF_ID': '000602090', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ahmet', 'LastName': 'Cetin', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ahmet E Cetin', 'EmailAddress': '[email protected]', 'NSF_ID': '000723502', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'ASLIHAN', 'LastName': 'KARATAS', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'ASLIHAN KARATAS', 'EmailAddress': '[email protected]', 'NSF_ID': '000739378', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Lauryn', 'LastName': 'Spearing', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lauryn A Spearing', 'EmailAddress': '[email protected]', 'NSF_ID': '000881232', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Yu', 'LastName': 'Hou', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yu Hou', 'EmailAddress': '[email protected]', 'NSF_ID': '000918213', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Illinois at Chicago', 'CityName': 'CHICAGO', 'ZipCode': '606124305', 'PhoneNumber': '3129962862', 'StreetAddress': '809 S MARSHFIELD AVE M/C 551', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'IL07', 'ORG_UEI_NUM': 'W8XEAJDKMXH3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ILLINOIS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Illinois at Chicago', 'CityName': 'CHICAGO', 'StateCode': 'IL', 'ZipCode': '606124305', 'StreetAddress': '809 S MARSHFIELD AVE M/C 551', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'IL07'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~74996
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431169.xml'}
|
CISE MSI: RCBP: III: Advancing Speech Detection: A Hybrid Approach Using Large Language Models and Graph Neural Networks
|
NSF
|
01/01/2025
|
12/31/2026
| 400,000 | 400,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Michelle Rogers', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032920000'}
|
Online speech that threatens persons, groups, or organizations necessitates sophisticated tools for effective detection and mitigation. This project aims to construct an advanced hybrid machine learning pipeline to enhance the analysis of speech and detection of speech differences in online environments. The project focuses on three key aspects: detecting the characteristics of individual speech posts, understanding and mitigating the spread of threatening speech, and addressing the lack of comprehensive multilingual datasets, particularly for English and Spanish-speaking communities. By combining the analytical capabilities of Large Language Models (LLMs) for content analysis with Graph Neural Networks (GNNs) for understanding social dynamics, this project develops a robust suite of tools adaptable to various speech detection scenarios. Additionally, it creates and publishes new datasets that expand the coverage of speech analysis in English and fill the critical gap in speech research for the Spanish-speaking environment.<br/><br/>This project advances speech detection research through an effective hybrid machine learning pipeline. It focuses on three main objectives: enhancing the accuracy and reliability of threat detection using Large Language Models (LLMs), understanding the dynamics of threat propagation with Graph Neural Networks (GNNs), and creating a comprehensive multilingual dataset suite for threat detection. The LLMs analyze both explicit and implicit speech across various classes in multilingual contexts, primarily focusing on English and Spanish. The GNNs identify the origins and patterns of attacks in speech, predict its spread and trajectory, and develop strategies to mitigate its effects. The multilingual dataset suite supports diverse speech themes, ensuring balanced diversity and addressing size limitations.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/30/2024
|
07/30/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2431176
|
[{'FirstName': 'Megan', 'LastName': 'Richardson', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Megan S Richardson', 'EmailAddress': '[email protected]', 'NSF_ID': '000753975', 'StartDate': '07/30/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Zhiqian', 'LastName': 'Chen', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zhiqian Chen', 'EmailAddress': '[email protected]', 'NSF_ID': '000853094', 'StartDate': '07/30/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Taoran', 'LastName': 'Ji', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Taoran Ji', 'EmailAddress': '[email protected]', 'NSF_ID': '000996192', 'StartDate': '07/30/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Texas A&M University Corpus Christi', 'CityName': 'CORPUS CHRISTI', 'ZipCode': '784125739', 'PhoneNumber': '3618252730', 'StreetAddress': '6300 OCEAN DR UNIT 5739', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '27', 'CONGRESS_DISTRICT_ORG': 'TX27', 'ORG_UEI_NUM': 'Y3RET2XN41S5', 'ORG_LGL_BUS_NAME': 'TEXAS A&M UNIVERSITY-CORPUS CHRISTI', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Texas A&M University Corpus Christi', 'CityName': 'CORPUS CHRISTI', 'StateCode': 'TX', 'ZipCode': '784125739', 'StreetAddress': '6300 OCEAN DR UNIT 5739', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '27', 'CONGRESS_DISTRICT_PERF': 'TX27'}
|
{'Code': '173Y00', 'Text': 'CISE MSI Research Expansion'}
|
2024~400000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431176.xml'}
|
AGS-CIF: Mobile Rapid Scanning Radar (RaXPol) for Enhancing Weather Radar Research and Hands-on Education
|
NSF
|
09/01/2024
|
08/31/2029
| 1,316,982 | 262,308 |
{'Value': 'Cooperative Agreement'}
|
{'Code': '06020300', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'AGS', 'LongName': 'Div Atmospheric & Geospace Sciences'}}
|
{'SignBlockName': 'Nicholas Anderson', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924715'}
|
The Division of Atmospheric and Geospace Sciences (AGS) operates the Community Instruments and Facilities (CIF) program to enhance the scientific community’s access to instrumentation that is otherwise too costly or complicated to operate for most institutions. This award is for the University of Oklahoma’s Rapid scan X-band Polarimetric (RaXPol) radar. RaXPol is a mobile radar with fast-scanning ability, making it ideal for studying tornadoes, hail, and lightning, along with many other weather-related topics. Wider use of RaXPol under the CIF program will provide additional information on societally-impactful weather, with a goal of improving forecasts of hazards to life and property. The use of RaXPol in outreach events will engage students at all levels, introducing both meteorological and engineering sciences. <br/><br/>RaXPol is a mobile, dual-polarization, Doppler radar with high sensitivity and fast scanning ability. The radar can provide a 20 second update of radar products over a volume of 360 degrees and 10 elevation angles. Recent and planned upgrades to the system, including a new transmitter and use of pulse compression techniques will further enhance the sensitivity of the system. RaXPol is well-suited for studies of tornadoes, hailstorms, convective initiation and updraft evolution, thunderstorm electrification, tropical cyclones, winter precipitation processes, fire plumes, and precipitation measurements in complex terrain. The radar will be available for request by the scientific community through the US NSF’s Facility and Instrumentation Request Process.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
CoopAgrmnt
|
47.050
|
1
|
4900
|
4900
|
2431179
|
[{'FirstName': 'Robert', 'LastName': 'Palmer', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robert D Palmer', 'EmailAddress': '[email protected]', 'NSF_ID': '000362067', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Howard', 'LastName': 'Bluestein', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Howard B Bluestein', 'EmailAddress': '[email protected]', 'NSF_ID': '000098989', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'David', 'LastName': 'Bodine', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David J Bodine', 'EmailAddress': '[email protected]', 'NSF_ID': '000603622', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Tian-You', 'LastName': 'Yu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tian-You Yu', 'EmailAddress': '[email protected]', 'NSF_ID': '000403396', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Pierre', 'LastName': 'Kirstetter', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Pierre Kirstetter', 'EmailAddress': '[email protected]', 'NSF_ID': '000731987', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Oklahoma Norman Campus', 'CityName': 'NORMAN', 'ZipCode': '730193003', 'PhoneNumber': '4053254757', 'StreetAddress': '660 PARRINGTON OVAL RM 301', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oklahoma', 'StateCode': 'OK', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'OK04', 'ORG_UEI_NUM': 'EVTSTTLCEWS5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF OKLAHOMA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Oklahoma Norman Campus', 'CityName': 'NORMAN', 'StateCode': 'OK', 'ZipCode': '730193003', 'StreetAddress': '660 PARRINGTON OVAL RM 301', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oklahoma', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'OK04'}
|
[{'Code': '164200', 'Text': 'Special Initiatives'}, {'Code': '689700', 'Text': 'AGS-ATM & Geospace Sciences'}]
|
2024~262308
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431179.xml'}
|
I-Corps: Translation Potential of an Automated Handling and Feeding Technology for Skewering Operations in Kebab Production
|
NSF
|
09/01/2024
|
08/31/2025
| 50,000 | 50,000 |
{'Value': 'Standard Grant'}
|
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
|
{'SignBlockName': 'Jaime A. Camelio', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922061'}
|
The broader impact of this I-Corps project is the development of an unattended production line to produce different kebabs with various meat, seafood, and vegetable combinations. In 2021, U.S. domestic per capita red meat and chicken consumption was 208 pounds, of which chicken (46%), beef (28%), and pork (24%) comprised the greatest fractions. The U.S. also has the largest seafood market globally, with $70 billion consumed in 2017. Shrimp had the greatest retail supermarket sales ($4,921 million) in 2020–2021. However, the U.S. meat and seafood industries face challenges in enhancing profitability due to international market competition and overproduction. Moreover, the outbreak of COVID-19 revealed a sharp decline in the labor force for the entire food industry. For U.S. meat and seafood processors to stay profitable and competitive, an increased level of automation is needed for value-added production. Currently, a kebab production line needs 5-10 operators for the manual preparation process. Realizing an automated process can save labor costs. Moreover, with appropriate adjustments, this automation system can be applied to all U.S. meat and seafood species. <br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of an automated handling and feeding process to automate the skewering operations for meat cubes, vegetable slices, and shrimp that would be difficult to realize via commercially available production means. Currently, most skewering machines need manual placement and alignment of food items during processing. Fully automated skewering machines have high error rates and high manufacturing costs and cannot handle and process shrimp. The newly developed system is the first unattended kebab production line to process shrimp, and the first design using a horizontal skewering operation to produce meat and vegetable kebabs and shrimp and vegetable kebabs. The solution can be freely integrated with skewering machines, which have the potential to benefit the U.S. meat and seafood processors by minimizing labor dependence and costs.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/22/2024
|
07/22/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2431189
|
{'FirstName': 'Wenbo', 'LastName': 'Liu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Wenbo Liu', 'EmailAddress': '[email protected]', 'NSF_ID': '000933276', 'StartDate': '07/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Mississippi State University', 'CityName': 'MISSISSIPPI STATE', 'ZipCode': '39762', 'PhoneNumber': '6623257404', 'StreetAddress': '245 BARR AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Mississippi', 'StateCode': 'MS', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'MS03', 'ORG_UEI_NUM': 'NTXJM52SHKS7', 'ORG_LGL_BUS_NAME': 'MISSISSIPPI STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Mississippi State University', 'CityName': 'MISSISSIPPI STATE', 'StateCode': 'MS', 'ZipCode': '39762', 'StreetAddress': '245 BARR AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Mississippi', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'MS03'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431189.xml'}
|
CIVIC-PG Track A: From Vulnerability to Resilience: Advancing Multi-Hazard Risk Mapping for Disaster-Resilient Communities in Mississippi
|
NSF
|
10/01/2024
|
03/31/2025
| 74,999 | 74,999 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Daan Liang', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922441'}
|
The objective of this Civic Innovation Challenge Planning Grant (CIVIC-PG) is to support research on multi-hazard risk analysis, which involves the examination of multiple hazards in a specific geographic area and time, their magnitude, their interactions, and the interpretation of their combined effects on the local communities. Many parts of the United States have seen an increasing number of weather and climate disasters, from severe storms and floods to heat waves and droughts. The Mississippi Delta is particularly vulnerable to such disasters, which significantly impact the natural environment and anthropogenic resources. Vulnerability is driven by a combination of factors, including economically disadvantaged and marginalized populations, systemic issues, limited resources, and lack of understanding of risk. This project envisions building disaster-resilient communities by developing advanced, community-driven, open-source multi-hazard risk assessment tools. These tools are critical to developing effective strategies for disaster risk reduction, infrastructure design, urban planning, climate change adaptation, and sustainable economic development. <br/><br/>The project establishes a robust partnership between the university and the community to identify social, economic, political, and governance factors that hinder the resilience of the Mississippi Delta communities. Researchers and stakeholders co-develop methods to incorporate local knowledge and contextual understanding of multi-hazard risk into research, policy, and practice. Using web interactive mapping applications, the project harnesses the potential and capabilities of remote sensing and open geospatial data, machine learning algorithms, and cloud computing for risk identification and visualization. The project also addresses the effect of spatial scale on the quantification of multi-hazard risk and researches a fractal-based modeling framework for multi-scale risk assessment.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/17/2024
|
07/17/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2431193
|
[{'FirstName': 'Gregg', 'LastName': 'Davidson', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Gregg R Davidson', 'EmailAddress': '[email protected]', 'NSF_ID': '000187769', 'StartDate': '07/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Thomas', 'LastName': 'Oommen', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Thomas Oommen', 'EmailAddress': '[email protected]', 'NSF_ID': '000573263', 'StartDate': '07/17/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Lance', 'LastName': 'Yarbrough', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lance D Yarbrough', 'EmailAddress': '[email protected]', 'NSF_ID': '000793742', 'StartDate': '07/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Meagen', 'LastName': 'Rosenthal', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Meagen Rosenthal', 'EmailAddress': '[email protected]', 'NSF_ID': '000831595', 'StartDate': '07/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Mississippi', 'CityName': 'UNIVERSITY', 'ZipCode': '386779704', 'PhoneNumber': '6629157482', 'StreetAddress': '113 FALKNER', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Mississippi', 'StateCode': 'MS', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'MS01', 'ORG_UEI_NUM': 'G1THVER8BNL4', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY OF MISSISSIPPI', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Mississippi', 'CityName': 'UNIVERSITY', 'StateCode': 'MS', 'ZipCode': '386779704', 'StreetAddress': '100 Barr Hall', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Mississippi', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'MS01'}
|
[{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}, {'Code': '138500', 'Text': 'SSA-Special Studies & Analysis'}]
|
2024~74999
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431193.xml'}
|
CIVIC-PG Track B: Enhancing Digital Inclusion in Rural Tribal Communities with Dynamically Reliable Mobile Broadband
|
NSF
|
10/01/2024
|
03/31/2025
| 74,992 | 74,992 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Vishal Sharma', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928950'}
|
This project focuses on improving access to Internet and digital services among rural tribal communities, which are historically some of the communities most underserved by Internet in the United States. Effectively using digital services to access critical health, educational, and other social services requires both access to affordable, reliable broadband infrastructure as well as the training and support to take advantage of that infrastructure. Recognizing the high cost and complexity of extending traditional, always available, Internet infrastructure to the hardest-to-reach, in this project we propose an alternative: dynamically reliable Internet access, a supplemental form of network infrastructure that provides predictable, reliable, but periodic Internet service to otherwise unserved locations at a fraction of the cost of traditional permanent Internet infrastructure. We couple this with outreach efforts to provide digital skills training on location to people served by this supplemental network service, thus ensuring newly-served populations can make effective use of this infrastructure.<br/><br/>In this pilot project, we partner with the Nez Perce Tribe and Nez Perce Network Systems, a Tribal utility providing Internet service, to design a dynamically reliable cellular network and to extend their existing digital skills training and support program to provide on-site support with tribal elders where they reside. We will leverage the Nez Perce Tribe’s existing fixed network infrastructure to support this network, along with the Tribe’s extensive 2.5GHz radio frequency spectrum holdings. In doing so, we will explore what dimensions of reliability are relevant in the context of digital inclusion and expand the binary notion of "reliability" operationalized in contexts such as federal digital equity policy to a design space to allow network operators to match technical affordances of low-cost network infrastructure with user needs within their community.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track B. Bridging the gap between essential resources and services & community needs and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/02/2024
|
08/02/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2431206
|
{'FirstName': 'Shaddi', 'LastName': 'Hasan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shaddi Hasan', 'EmailAddress': '[email protected]', 'NSF_ID': '000852831', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Virginia Polytechnic Institute and State University', 'CityName': 'BLACKSBURG', 'ZipCode': '240603359', 'PhoneNumber': '5402315281', 'StreetAddress': '300 TURNER ST NW', 'StreetAddress2': 'STE 4200', 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'VA09', 'ORG_UEI_NUM': 'QDE5UHE5XD16', 'ORG_LGL_BUS_NAME': 'VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'M515A1DKXAN8'}
|
{'Name': 'Virginia Polytechnic Institute and State University', 'CityName': 'BLACKSBURG', 'StateCode': 'VA', 'ZipCode': '240611050', 'StreetAddress': '620 Drillfield Drive', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'VA09'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~74992
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431206.xml'}
|
CIVIC-PG Track A: Building Community Resilience to Drought, Population Growth, and Cascading Water Quality Challenges in a Large One-Water System
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Vishal Sharma', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928950'}
|
Historically, water systems in urban communities have been thought about, regulated, and managed as three distinct sub-systems: drinking water, wastewater, and stormwater. Practitioners throughout the world are increasingly embracing the idea of integrated management of these three subsystems with the end goals of improving water quality, increasing water supply reliability, reducing freshwater withdrawal, and achieving energy and cost savings. However, widespread adoption of this integrated “One Water” vision will require a radical departure from the siloed way these systems are typically managed. This CIVIC project will foster a technology- and community-centered approach for managing cascading water quality risks in the Occoquan Reservoir, a source of drinking water for up to 1 million people in Northern Virginia. To accomplish this, we will work with local communities to identify concerns and potential solutions to the water quality challenges facing this critical water supply. We will then pilot test a new water quality modeling framework with our community partners. The modeling framework will serve as the centerpiece of a generalizable system-of-systems approach for managing emerging contaminants and other acute and chronic water quality challenges in One Water systems.<br/><br/>Our vision for managing water quality risks in One Water systems is predicated on an ability to link upstream pollution sources to downstream water quality, ideally in real time. Models of pollutant fate and transport through reservoirs typically take the form of software packages that numerically solve momentum, energy and mass conservation equations, empirical models, machine learning approaches, or multi-model ensembles. The approach proposed here, transient transit time distribution (T-TTD) theory, takes an entirely different tack by tracking the flux and age distribution of water and pollutants moving into and out of a control volume drawn around the reservoir. By eliminating the need to describe within reservoir transport processes, T-TTD theory vastly simplifies model development, reduces computational requirements for real-time deployment, and opens the door to unbiased assessment of model structure and parameter inference. It is also strongly data driven and thus leverages the high-frequency flow and water quality monitoring data routinely collected in One Water systems. Co-production of this modeling framework will ensure that it is salient, credible, and legitimate for decision-making. The goal is to provide communities and practitioners with the actionable information they need to manage cascading water quality risks in more integrated and equitable ways, both now and under various population growth and climate change scenarios.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/02/2024
|
08/02/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2431213
|
[{'FirstName': 'Stanley', 'LastName': 'Grant', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Stanley B Grant', 'EmailAddress': '[email protected]', 'NSF_ID': '000473309', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Shantanu', 'LastName': 'Bhide', 'PI_MID_INIT': 'V', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shantanu V Bhide', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A07QB', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Hannah', 'LastName': 'Whitley', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hannah Whitley', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A07Q9', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Megan', 'LastName': 'Rippy', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Megan A Rippy', 'EmailAddress': '[email protected]', 'NSF_ID': '000797285', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Todd', 'LastName': 'Schenk', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Todd Schenk', 'EmailAddress': '[email protected]', 'NSF_ID': '000740373', 'StartDate': '08/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Virginia Polytechnic Institute and State University', 'CityName': 'BLACKSBURG', 'ZipCode': '240603359', 'PhoneNumber': '5402315281', 'StreetAddress': '300 TURNER ST NW', 'StreetAddress2': 'STE 4200', 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'VA09', 'ORG_UEI_NUM': 'QDE5UHE5XD16', 'ORG_LGL_BUS_NAME': 'VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'M515A1DKXAN8'}
|
{'Name': 'Virginia Polytechnic Institute and State University', 'CityName': 'Manassas', 'StateCode': 'VA', 'ZipCode': '201105666', 'StreetAddress': '9408 Prince William St', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'VA10'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431213.xml'}
|
EAGER: TaskDCL: Personalized Robotic Assistance: Developing Safe, User-Taught Functionalities for Diverse Needs
|
NSF
|
09/01/2024
|
08/31/2026
| 300,000 | 300,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Alex Leonessa', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922633'}
|
In the era of advanced robotics and AI, there is a notable gap in leveraging these technologies for personalized human assistance, especially in settings that require nuanced understanding. Current robotic systems, despite their impressive locomotion capabilities, often lack the flexibility needed to adapt to the diverse needs of users, as their interactions are typically restricted to predefined functionalities. This limitation is particularly evident in scenarios where humans teach robots to perform highly personalized tasks within shared physical spaces, which may lead to discomfort and safety concerns among users. This EArly-concept Grant for Exploratory Research (EAGER) project will fund research that attempts to address the challenging task of a quadrotor to pick up/drop off a small package from/onto a human's outstretched hand following the human's instructions. The challenge of the task comes from the quadrotor's close proximity to a human, which can trigger stress due to noise and movement, potentially undermining task completion. The research effort seeks to address the above-mentioned task utilizing a framework that enables anyone to safely instruct robots in customized tasks. This research is crucial for the exploration of harnessing the intelligence enabled by machine learning to expand the capabilities of robots toward humans’ needs, especially in the industries that urge rapidly growing robot participation and coordination with humans, e.g., manufacturing, logistics, transportation, and national defense.<br/><br/>This research aims to attain the objective of allowing quadrotors to safely interact with people for the chosen task of direct hand-to-hand package delivery, ultimately leading to robots that can genuinely adapt to and meet individual needs for more personalized and safe human-robot interactions. The researched effort incorporates the human's cognitive state into the quadrotor's decision-making and action processes, fostering a bidirectional sensorimotor interaction and allowing both the human and the quadrotor to sense and influence each other's decisions and actions while the quadrotor conducts the task in close proximity to the human. Two interconnected research thrusts will be pursued: (i) planning and control for safe human-robot interaction with models for human cognitive states and (ii) iterative learning for enhanced performance towards efficient and safe human-robot interactions. The research framework builds upon the advances made by the PIs in control theory/engineering and psychology and is expected to make important contributions to the society of the future, in which humans and robots behave and interact safely and effectively while occupying shared spaces.<br/><br/>This EAGER award has been co-funded by the Dynamics, Controls, and System Diagnostics and the Mind, Machine, and Motor Nexus Programs.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2431216
|
[{'FirstName': 'Ranxiao', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ranxiao Wang', 'EmailAddress': '[email protected]', 'NSF_ID': '000166426', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Naira', 'LastName': 'Hovakimyan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Naira Hovakimyan', 'EmailAddress': '[email protected]', 'NSF_ID': '000494200', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'University of Illinois at Urbana-Champaign', 'CityName': 'URBANA', 'ZipCode': '618013620', 'PhoneNumber': '2173332187', 'StreetAddress': '506 S WRIGHT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'IL13', 'ORG_UEI_NUM': 'Y8CWNJRCNN91', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ILLINOIS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Illinois at Urbana-Champaign', 'CityName': 'URBANA', 'StateCode': 'IL', 'ZipCode': '618013620', 'StreetAddress': '506 S WRIGHT ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_PERF': 'IL13'}
|
[{'Code': '058Y00', 'Text': 'M3X - Mind, Machine, and Motor'}, {'Code': '756900', 'Text': 'Dynamics, Control and System D'}]
|
2024~300000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431216.xml'}
|
Planning: SCC-CIVIC-PG Track B: Manufacturing Automation Toolkit (MAT): Enhancing Equity through Collaborative Visioning in Manufacturing Future
|
NSF
|
10/01/2024
|
03/31/2025
| 72,922 | 72,922 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Ralph Wachter', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928950'}
|
Robotics and AI technologies have rapidly reconfigured workplaces. The manufacturing industry is at the forefront of these changes. Although these technologies have the potential to significantly reduce labor intensity and improve work efficiency, workers often lack the resources to learn about, envision, and prepare for their integration into daily work, leading to concerns and missed opportunities for process innovation and empowerment. This project offers a novel approach to engage the workforce through technology innovations, learn about these technologies, and simulate workplace change. This stage 1 planning grant is conducted in cooperation with United Auto Workers (UAW) Local 602, the State of Michigan, Rockwell Automation, manufacturing industry partners, and manufacturing community.<br/> <br/>The stage 1 planning grant focuses on understanding production workers’ concerns through interviews, observation, and building multidisciplinary teams as the project stakeholders develop the technical requirements for (1) a “digital twin” model for visualizing how new automation technologies would change the workflow and that allows workers to experience the change in a virtual environment, (2) a generative AI that answers workers’ questions about automation technologies, and (3) a catalog of emerging automation technologies in manufacturing, made accessible to workers for exploring and learning about new technologies. The stage 2 project would build a prototype system and pilot it at automative manufacturing facility.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track B. Bridging the gap between essential resources and services & community needs and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2431223
|
[{'FirstName': 'Wenlong', 'LastName': 'Zhang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Wenlong Zhang', 'EmailAddress': '[email protected]', 'NSF_ID': '000706436', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Hee Rin', 'LastName': 'Lee', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hee Rin Lee', 'EmailAddress': '[email protected]', 'NSF_ID': '000820618', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'ZipCode': '488242600', 'PhoneNumber': '5173555040', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MI07', 'ORG_UEI_NUM': 'R28EKN92ZTZ9', 'ORG_LGL_BUS_NAME': 'MICHIGAN STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'VJKZC4D1JN36'}
|
{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'StateCode': 'MI', 'ZipCode': '488242600', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MI07'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~72922
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431223.xml'}
|
SCC-CIVIC-PG Track A: Enhancing Oklahoma Community Climate Resilience Through Electric School Bus Integration into Local Energy Grids
|
NSF
|
10/01/2024
|
03/31/2025
| 74,999 | 74,999 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'David Corman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928754'}
|
Oklahoma faces frequent extreme weather events like tornadoes and storms, disrupting the state's energy grid. This project seeks to enhance community resilience against climate and environmental instabilities by integrating the Vehicle-to-Grid (V2G) technology equipped with electric school buses (ESBs) into Oklahoma energy grids. V2G technology allows these ESBs to supply power back to the grid, offering a sustainable energy solution. This initiative aims to flip the community-university dynamic and empower civic partners to co-design a research-to-innovation solution to improving grid stability during emergencies, reduce greenhouse gas emissions, and promote public health. By showcasing the benefits of V2G in a real-world setting, the project could serve as a model for other regions. This work aligns with NSF’s mission to promote the progress of science by investing in research to expand knowledge in science, engineering and education. This work is not only critical for addressing immediate climate-related challenges but also for building a resilient and sustainable future for communities.<br/><br/>The project will integrate V2G-equipped electric school buses (ESBs) into Oklahoma’s energy grid to enhance community resilience to climate disasters such as tornados and storms. In Stage 1, a Community Advisory Board (CAB) with stakeholders from Public Schools, Oklahoma Gas & Electric, Association of Central Oklahoma Governments, Indian Nations Council of Governments, City of Oklahoma City, ESB Manufacturers and other community partners will co-design the research plan, set goals, and refine research questions. Preliminary testing and data collection will be conducted to understand community needs and technical requirements. In Stage 2, field tests and simulations will assess the effectiveness of V2G technology during power outages and peak demand. The project will analyze economic and environmental benefits, including cost savings and reduced greenhouse gas emissions, and develop a decision-making support platform for policymakers. By leveraging civic partners’ expertise, the project aims to create a scalable model for community resilience through innovative energy solutions.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/08/2024
|
08/08/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2431225
|
[{'FirstName': 'Hamidreza', 'LastName': 'Nazaripouya', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hamidreza Nazaripouya', 'EmailAddress': '[email protected]', 'NSF_ID': '000795331', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Dong', 'LastName': 'Zhang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dong Zhang', 'EmailAddress': '[email protected]', 'NSF_ID': '000870335', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Hongwan', 'LastName': 'Li', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hongwan Li', 'EmailAddress': '[email protected]', 'NSF_ID': '000947323', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Changjie', 'LastName': 'Cai', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Changjie Cai', 'EmailAddress': '[email protected]', 'NSF_ID': '000804950', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ardeshir', 'LastName': 'Moftakhari', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ardeshir Moftakhari', 'EmailAddress': '[email protected]', 'NSF_ID': '000937805', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Oklahoma Health Sciences Center', 'CityName': 'OKLAHOMA CITY', 'ZipCode': '731043609', 'PhoneNumber': '4052712090', 'StreetAddress': '865 RESEARCH PKWY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oklahoma', 'StateCode': 'OK', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'OK05', 'ORG_UEI_NUM': 'GY8NMUZQXVS7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF OKLAHOMA', 'ORG_PRNT_UEI_NUM': 'GY8NMUZQXVS7'}
|
{'Name': 'University of Oklahoma Health Sciences Center', 'CityName': 'OKLAHOMA CITY', 'StateCode': 'OK', 'ZipCode': '731043609', 'StreetAddress': '865 RESEARCH PKWY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oklahoma', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'OK05'}
|
[{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}, {'Code': '164000', 'Text': 'Information Technology Researc'}]
|
2024~74999
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431225.xml'}
|
Planning: CREST Center for Sustainable and Green Electrochemical Science and Technology
|
NSF
|
09/01/2024
|
08/31/2026
| 199,999 | 199,999 |
{'Value': 'Standard Grant'}
|
{'Code': '03090000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'CHE', 'LongName': 'Division Of Chemistry'}}
|
{'SignBlockName': 'Michelle Bushey', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924285'}
|
In this project, jointly funded by the Broadening Participation Program in the Division of Chemistry (BP-CHE) and the Centers of Research Excellence in Science and Technology program (CREST) in the Division of Equity for Excellence in STEM (EES), Professor Zhange Feng and his colleagues at the University of Nevada, Las Vegas (UNLV) will conduct planning activities aimed at establishing a Center of Research Excellence in Science and Technology focused on Chemistry research (CREST-CHE). The proposed center will concentrate on sustainable and ecofriendly electrochemical science and technology. The ultimate goal of the CREST-CHE is to drive institutional transformation by enhancing the research capacities in electrochemical science and technology, aligning with the overarching objectives of UNLV.<br/><br/>A series of planning activities are proposed, aiming to prepare a competitive full proposal to the CREST center with the completion of the planning activities. Three types of meetings are scheduled to devise the strategy, align the objective, and foster collaborative research among the team members, including semi-annual strategic planning meetings, bi-monthly progress review meetings, and biweekly collaboration meetings. Additionally, training opportunities in the form of workshops and symposiums are provided to faculty members and students to better prepare the team for the comprehensive proposal. The team will also conduct a thorough evaluation of infrastructures and resources at UNLV, and the conclusion will be included in the full proposal to ensure the success of the CREST center. Collaborative research among the team members will be conducted to gather preliminary data, including research on electrochemical energy storage, electrochemical CO2 reduction, organic electrosynthesis of compounds containing P-F bonds, electrochemical separation, and theoretical calculations. The success of the proposed planning activities will lead to a highly capable team in electrochemical science and technology, empowering PIs to craft a competitive proposal for the CREST center.<br/><br/>Through the strategy formulated in the planning activities, the project will seek to enroll a large number of undergraduate and graduate students that are reflective of the institution's overall student demographics. The project will significantly enhance the curriculum development and prepare students to work in the highly interdisciplinary area related to electrochemical science and technology. It will provide unique training opportunities through workshops and symposiums for faculty members and students working in electrochemical science and technology. The project will also inspire the next generation of scientists and engineers by engaging high school students from the local school district through a summer internship programs at UNLV.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/27/2024
|
08/27/2024
|
None
|
Grant
|
47.049, 47.076
|
1
|
4900
|
4900
|
2431226
|
[{'FirstName': 'Jun', 'LastName': 'Kang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jun Kang', 'EmailAddress': '[email protected]', 'NSF_ID': '000724918', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Zhange', 'LastName': 'Feng', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zhange Feng', 'EmailAddress': '[email protected]', 'NSF_ID': '000838805', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Jared', 'LastName': 'Bruce', 'PI_MID_INIT': 'P', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jared P Bruce', 'EmailAddress': '[email protected]', 'NSF_ID': '000898103', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Chern', 'LastName': 'Chuang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Chern Chuang', 'EmailAddress': '[email protected]', 'NSF_ID': '000983096', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'matthew', 'LastName': 'sheridan', 'PI_MID_INIT': 'V', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'matthew V sheridan', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A07FT', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Nevada Las Vegas', 'CityName': 'LAS VEGAS', 'ZipCode': '891549900', 'PhoneNumber': '7028951357', 'StreetAddress': '4505 S MARYLAND PKWY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Nevada', 'StateCode': 'NV', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NV01', 'ORG_UEI_NUM': 'DLUTVJJ15U66', 'ORG_LGL_BUS_NAME': 'BOARD OF REGENTS OF NEVADA SYSTEM OF HIGHER EDUCATION', 'ORG_PRNT_UEI_NUM': 'F995DBS4SRN3'}
|
{'Name': 'University of Nevada Las Vegas', 'CityName': 'LAS VEGAS', 'StateCode': 'NV', 'ZipCode': '891549900', 'StreetAddress': '4505 S MARYLAND PKWY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Nevada', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NV01'}
|
[{'Code': '748700', 'Text': 'BROADENING PARTICIPATION'}, {'Code': '913100', 'Text': 'Centers for Rsch Excell in S&T'}]
|
2024~199999
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431226.xml'}
|
CIVIC-PG Track A: Building resilient Arctic communities to permafrost thaw hazards
|
NSF
|
10/01/2024
|
03/31/2025
| 74,816 | 74,816 |
{'Value': 'Standard Grant'}
|
{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}
|
{'SignBlockName': 'Barbara Ransom', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927792'}
|
Warming Arctic temperatures are causing permafrost regions of the far north latitudes to thaw for the first time in millennia. Permafrost consists of frozen sediments that, when temperatures rise like they are now, causes the ice inside them to melt. Ice-like minerals, called clathrates, that abound in permafrost, also decompose and release additional water and methane. The combination of liquefaction of the sediment and corresponding decrease in sediment volume causes deflation resulting in ground instability and subsidence or collapse of the land surface. At present, most communities across Alaska do not have good understanding of permafrost or a comprehensive and consistent approach to understanding permafrost and its impact on infrastructure and how to potentially mitigate its effects, especially communities in rural areas with small numbers of people; those that are unincorporated with limited local government and technological resources; and those without adequate access to or knowledge of data resources that would allow them to identify locations of vulnerability to permafrost collapse or determine the best ways to avoid or address it. <br/>In some cases, permafrost decomposition has led to the closure of roads, airfields, hospitals, and other essential infrastructure components, requiring relocation and/or costly repairs. For these communities, detailed and up-to-date map products and access to information on permafrost areas and the impacts of its decomposition in a warming Arctic are essential in emergency response and long-term planning for any community. This Civic Innovation Challenge (CIVIC) planning process brings scientists and Arctic indigenous people and their representing organizations and other interested parties together to co-design an Alaskan hazard map that can be used to identify permafrost areas that can put communities in peril and can identify safe locations for the relocation of structures and permafrost compromised buildings and installations. Such a map would provide a much needed high-resolution tool to help improve Alaskan community resilience and inform their planning and possible relocation of people and infrastructure for the future in a rapidly warming Arctic. One project goal is to co-design a map and application that could be used by anyone, regardless of the user’s technical or financial resources. The planning process will develop the conceptual framework for a follow-in implementation project that would provide guidance and information for any community in Alaska. The final product would include information on what data people should to look for and look at, where to find it, and how to interact with; use; and apply that data for permafrost thaw hazard assessment and planning. The planning project will build upon the existing Permafrost Discovery Gateway imagery platform that is hosted by the Arctic Research Consortium of the United States. This is a free online resource that aims to enable big geospatial data creation and knowledge-generation. Interviews with project participants and co-design of the application will help support community discovery of fine resolution maps of ground subsidence rates obtained from satellite imagery analyses. The project team will also explore new AI tools that could support communities. Broader impacts of the project include development of a tool to help Alaskans discover areas at high risk and vulnerability to permafrost decomposition due to climate change, and improve community resilience; planning; protection; and relocation of assets and homes to areas free of permafrost. <br/><br/>The goal of this Civic Innovation Challenge (CIVIC) planning period is to bring together key stakeholders from across Alaska and from the Arctic science community to co-design the elements, applications, the user interface, and visualizations of a meter-scale, high-resolution, online, permafrost map, and a conceptualization framework and guidance document for Alaska and its permafrost impacted areas for a project that would be developed and implemented in a follow-on CIVIC proposal. This planning process will result in Alaskan community access to high-resolution, remote sensing and geospatial images and information on permafrost locations and where safe locations are for new infrastructure or the relocation of that which is already or soon to be compromised by permafrost decomposition. The online application will combine ground subsidence data gleaned from satellite interferometric synthetic aperture radar (InSAR) images. Algorithms will be created and implemented to optimize big data creation of workflows developed by Permafrost Discovery Gateway science members. This enables communities or researchers with limited technical expertise or resources to work with big geospatial data. Partners in design of the envisioned application include members of the Permafrost Discovery Gateway; the Alaska Coastal Cooperative; the Permafrost Pathways organization which was started with private funding and includes experts in climate science, policy action, and environmental justice; the Radar Remote Sensing Group at the University of Alaska Fairbanks; and the Coastal Villages Region Fund which represents 20 Alaskan communities along the Bering Sea coastline. This planning process is designed to improve the understanding of how community-based efforts can be designed to provide improved nature-based solutions to climate change and will foster and strengthen collaboration between researchers and community stakeholders, develop new collaborations and partnerships, refine the research vision to enable submission of a successful follow-on proposal that will implement the community vision, and provide information to address research questions and develop evaluation methods and measures for the follow-on project. <br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy. It was funded by the NSF Directorate for Geosciences.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/09/2024
|
08/09/2024
|
None
|
Grant
|
47.050
|
1
|
4900
|
4900
|
2431228
|
[{'FirstName': 'Anna', 'LastName': 'Liljedahl', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Anna K Liljedahl', 'EmailAddress': '[email protected]', 'NSF_ID': '000568813', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Simon', 'LastName': 'Zwieback', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Simon Zwieback', 'EmailAddress': '[email protected]', 'NSF_ID': '000828343', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Woodwell Climate Research Center, Inc.', 'CityName': 'FALMOUTH', 'ZipCode': '025401644', 'PhoneNumber': '5084441526', 'StreetAddress': '149 WOODS HOLE RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'MA09', 'ORG_UEI_NUM': 'F5HBB1KH19N4', 'ORG_LGL_BUS_NAME': 'WOODWELL CLIMATE RESEARCH CENTER INC', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Woodwell Climate Research Center, Inc.', 'CityName': 'FALMOUTH', 'StateCode': 'MA', 'ZipCode': '025401644', 'StreetAddress': '149 WOODS HOLE RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'MA09'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~74816
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431228.xml'}
|
SCC-CIVIC-PG Track B: Strengthening Peer-Run Community Mental Health Services for Marginalized Population through Participatory AI Design
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Vishal Sharma', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928950'}
|
Public and community mental health services, which provide essential support and treatment for individuals with behavioral health conditions, have a profound impact on communities and millions of individuals across the United States. Un- or under-treated, significant mental illnesses are among the biggest sources of years lost to disability and economic burden in the United States. Communities served by public and community mental health services represent some of the most vulnerable in our society and can benefit greatly from the development of data-driven intelligent technologies. This planning grant focuses on strengthening and empowering peer-led organizations in public and community mental health services. As the behavioral health workforce crisis deepens, there is a growing imperative to expand and enhance the role of peer providers in public behavioral health, particularly within underfunded and technologically under-resourced peer-led agencies. These organizations, vital for delivering a diverse range of support to address individual holistic needs, including social, physical, emotional, and environmental by offering individual peer support, self-help groups, education and training, navigation to legal advocacy, face significant challenges due to inadequate technological infrastructure and reliance on low-tech service delivery methods. <br/><br/>This planning grant builds on our ongoing partnership with Collaborative Support Programs of New Jersey (CSPNJ), a state-wide, peer-led community-based behavioral health agency, which is known for its innovative work serving people with complex behavioral health, social and economic challenges. We will work together to create community-centered AI solutions that meet the needs of both peer service providers and recipients in resource-constrained peer-led public mental health services. We aim to build a collective understanding of community needs, success criteria, and challenges, and facilitate rapid prototyping of proven AI solutions through participatory methods. Leveraging multidisciplinary expertise in Human-computer Interaction (HCI), Artificial Intelligence (AI), mental health, and social work, and in close collaboration with our community partners, this planning grant will help us gain a robust understanding of (1) how service providers and recipients perceive success in peer-run community mental health services and the challenges they face in achieving such success. Based on these insights, we will (2) collaboratively identify specific AI-driven technologies that could be piloted in Stage 2 to enhance the capabilities of safety-net peer-run organizations. This will empower them to better meet the needs of underserved communities and potentially serve a broader population, thereby strengthening their impact in the community mental health sector.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track B. Bridging the gap between essential resources and services & community needs and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/08/2024
|
08/08/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2431230
|
[{'FirstName': 'FEI', 'LastName': 'FANG', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'FEI FANG', 'EmailAddress': '[email protected]', 'NSF_ID': '000754062', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Hong', 'LastName': 'Shen', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hong Shen', 'EmailAddress': '[email protected]', 'NSF_ID': '000769644', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Carnegie-Mellon University', 'CityName': 'PITTSBURGH', 'ZipCode': '152133815', 'PhoneNumber': '4122688746', 'StreetAddress': '5000 FORBES AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'PA12', 'ORG_UEI_NUM': 'U3NKNFLNQ613', 'ORG_LGL_BUS_NAME': 'CARNEGIE MELLON UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'U3NKNFLNQ613'}
|
{'Name': 'Carnegie-Mellon University', 'CityName': 'PITTSBURGH', 'StateCode': 'PA', 'ZipCode': '152133815', 'StreetAddress': '5000 FORBES AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'PA12'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431230.xml'}
|
SCC-CIVIC-PG Track B: Community-based Gunshot Alert System
|
NSF
|
10/01/2024
|
03/31/2025
| 74,962 | 74,962 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'David Corman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928754'}
|
Gun violence and the reckless use of firearms have been a pervasive problem in the United States, especially in low-income communities. This problem has only become exacerbated by increasingly lax gun control laws, easy access to firearms, and growing mistrust of law enforcement that often inhibits reporting by the public. Gun-related crimes cost millions of dollars in medical expenses, law enforcement, and lost wages, not to mention the trauma and shattered lives they leave behind. Many gunshots go unreported or are difficult to identify and localize. Current commercial solutions to gunshot localization are expensive and out of the control of the local communities in which they are used. Motivated by real-world events in an economically disadvantaged community in Austin, Texas, this project seeks to build a community-based system for detecting, localizing, and classifying gunshots using a distributed network of inexpensive acoustic sensors connected via residents’ wireless internet services. The team will engage directly with the neighborhood community, law enforcement, and local government to provide a technological system and practical implementation that provides a scalable, sustainable, effective, and community-controlled solution to address the widespread prevalence of unsanctioned gunfire.<br/><br/>Building off pioneering work by Vanderbilt University in the area of wireless sensor network-based gunshot localization, the team will work with law enforcement and members of the community to determine both the community’s and the police department’s needs and concerns related to gun violence and to determine a path forward for creation of a system that adequately addresses both. To that end, the team will conduct surveys and organize a workshop with members of the community and law enforcement to develop system specifications in Phase 1. In Phase 2, a live pilot will further refine these specifications and lead to rapid system implementation based on an existing codebase and large library of urban gunshot recordings. This pilot system will be deployed in an Austin neighborhood, allowing the team to measure its technical efficacy and assess its impact on public safety and community attitudes. It will also provide a model for similar communities to adopt and adapt to their unique needs and circumstances. The research conducted under this project will advance the state of knowledge in low-cost gunshot localization technology and provide a valuable assessment of the impact and cost effectiveness of such systems when combined with a broad program of community engagement and education.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track B. Bridging the gap between essential resources and services & community needs and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/26/2024
|
07/26/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2431234
|
[{'FirstName': 'Will', 'LastName': 'Hedgecock', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Will Hedgecock', 'EmailAddress': '[email protected]', 'NSF_ID': '000710966', 'StartDate': '07/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Akos', 'LastName': 'Ledeczi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Akos Ledeczi', 'EmailAddress': '[email protected]', 'NSF_ID': '000348998', 'StartDate': '07/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Vanderbilt University', 'CityName': 'NASHVILLE', 'ZipCode': '372032416', 'PhoneNumber': '6153222631', 'StreetAddress': '110 21ST AVE S', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Tennessee', 'StateCode': 'TN', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'TN05', 'ORG_UEI_NUM': 'GTNBNWXJ12D5', 'ORG_LGL_BUS_NAME': 'VANDERBILT UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Vanderbilt University', 'CityName': 'NASHVILLE', 'StateCode': 'TN', 'ZipCode': '372032416', 'StreetAddress': '110 21ST AVE S', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Tennessee', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'TN05'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~74962
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431234.xml'}
|
CAREER: Zwitterionic Metal-Organic Frameworks with Multi-Stimulus-Responsive Properties
|
NSF
|
06/01/2024
|
02/28/2025
| 592,696 | 21,481 |
{'Value': 'Continuing Grant'}
|
{'Code': '03070000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMR', 'LongName': 'Division Of Materials Research'}}
|
{'SignBlockName': 'Birgit Schwenzer', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924771'}
|
Non-technical Abstract:<br/>This CAREER project is an integrated research, education, and outreach program funded by the Solid-State and Materials Chemistry program of the Division of Materials Research. The overall goal of the research plan is to devise strategies that enable the synthesis of a new class of advanced porous materials composed of charge-separated molecular building blocks. These charges can perform a desired function to attract specific guest molecules within the material's pores. In one line of research, the ability of light to interact with these charges will be explored to trigger the release of guest molecules to determine if the material can be regenerated to its original state. This feature would be particularly useful for a multitude of environmental applications that seek the adsorption or separation of gases, such as hydrogen storage and carbon capture respectively with the general objective to counteract global warming. Leveraging the research activities is the educational plan that will allow Clarkson University to offer a stronger, ACS-approved chemistry program, the foundation for a broad, rigorous chemistry education that provides students with the intellectual, experimental, and communication skills to become effective professionals. The outreach program is hands-on and incorporates state-of-the-art crystallography instrumentation to significantly strengthen and expand the high school to college pipeline for students from the rural North Country of New York State by increasing their exposure to and interest in STEM fields and careers. An X-ray diffraction workshop will provide participants with the training to understand and appropriately utilize the most precise method of determining crystal structures, thus allowing the analysis of fundamental structure-property relationship.<br/><br/>Technical Abstract:<br/>The proposed research plan addresses fundamental questions essential to the advancement of functional porous materials with multi-stimulus-responsive adsorption properties and rapid controllable release of guest molecules. Proposed is the use of zwitterionic metal-organic framework (ZW MOF) building blocks whose molecular surfaces show well-separated intramolecular charges with tunable electric field gradients. These gradients present potential multi-point adsorption sites that can be designed at a molecular level within the zwitterionic ligands prior to MOF self-assembly. Once zwitterions are incorporated into MOFs, their electric field gradients yield charged organic surfaces (COSs) within the pores, which in turn polarize guest molecules, resulting in defined adsorption properties. The most important feature of zwitterions is their sensitivity to external stimuli (e.g. light or electrochemical), resulting in switchable COSs that enable significant control and tunability of adsorption properties. Specific approaches are to: (1) Design and investigate ZW ligands as a new, simple, and controllable means to introduce COSs into pore linings to create MOFs with defined host-guest interactions; (2) Explore post-synthetic modification reactions as alternative routes for introducing ZW functionalities into MOFs; and (3) Demonstrate and optimize the multi-stimulus-responsive tunability of COSs by controllable release of guest molecules from MOF pores. These experiments will ultimately provide a powerful tool to tailor MOFs with tunable host-guest interactions and will generate fundamental knowledge on a novel type of multi-stimulus-responsive material with distinct adsorption and desorption properties.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
05/29/2024
|
05/29/2024
|
None
|
Grant
|
47.049
|
1
|
4900
|
4900
|
2431245
|
{'FirstName': 'Mario', 'LastName': 'Wriedt', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mario Wriedt', 'EmailAddress': '[email protected]', 'NSF_ID': '000671122', 'StartDate': '05/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Texas at Dallas', 'CityName': 'RICHARDSON', 'ZipCode': '750803021', 'PhoneNumber': '9728832313', 'StreetAddress': '800 WEST CAMPBELL RD.', 'StreetAddress2': 'SP2.25', 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '24', 'CONGRESS_DISTRICT_ORG': 'TX24', 'ORG_UEI_NUM': 'EJCVPNN1WFS5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF TEXAS AT DALLAS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Texas at Dallas', 'CityName': 'RICHARDSON', 'StateCode': 'TX', 'ZipCode': '750803021', 'StreetAddress': '800 WEST CAMPBELL RD.', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '24', 'CONGRESS_DISTRICT_PERF': 'TX24'}
|
[{'Code': '125300', 'Text': 'OFFICE OF MULTIDISCIPLINARY AC'}, {'Code': '176200', 'Text': 'SOLID STATE & MATERIALS CHEMIS'}]
|
2022~21481
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431245.xml'}
|
SCC-CIVIC-PG Track B: Data-Driven Monitoring and Optimizing of Right-of-Way Permits
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Vishal Sharma', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928950'}
|
Right-of-way closures, i.e., the closing of streets, bike lanes, sidewalks, and roads, frequently occur in urban areas due to construction projects, cargo delivery, and special events. Dynamic construction schedules, lack of compliance, and potentially outdated technological systems hinder the ability of city transportation authorities to effectively issue, monitor, and inspect permits, leading to compliance violations and traffic disruptions. The rate of permit violations is exceptionally high in urban areas, and the cost of these violations and the resulting inspections is staggering: Nashville Department of Transportation (NDOT) currently loses an estimated $2 million from the unpaid permit fees alone and pays external contractors an estimated $5 million annually for inspection. Most importantly, road closures (particularly illegal closures and violations) harm traffic, commuter safety, and local businesses. This problem is not restricted to Nashville alone; urban areas across the USA face challenges with enforcing and monitoring right-of-way closures. This project is a collaboration between Vanderbilt University, NDOT, the Metropolitan Government of Nashville, and Nashville Metropolitan Information Technology Services (ITS) to tackle these challenges through fundamental and civic-engaged research. Specifically, this project will design and develop data-driven artificial intelligence models that will 1) automate the detection of permit violations and 2) estimate the effects of right-of-way closures to optimize future permit issuance. <br/><br/>Our goal of automating the detection of right-of-way closures and estimating the impact of future closures requires fundamental advances in data science, machine learning, and software engineering. Specifically, the intellectual merit of our project lies in 1) the design and implementation of novel neural network architectures to automatically detect road closures; 2) the design and implementation of a data-driven approach to infer locations of road closures from heterogeneous and noisy crowdsourced data; 3) the development of an urban digital twin to estimate the effect of road closures in Nashville; 4) the development of an optimization engine for the issuance of right-of-way permits; and 5) system and data integration to deploy the proposed technology in Nashville. The resulting technical framework will be available for other urban areas, and it will apply to problems beyond right-of-way monitoring, e.g., emergency response and traffic management, and generally to the broader problem of monitoring societal-scale cyber-physical systems.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track B. Bridging the gap between essential resources and services & community needs and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/01/2024
|
08/01/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2431246
|
[{'FirstName': 'Daniel', 'LastName': 'Work', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Daniel B Work', 'EmailAddress': '[email protected]', 'NSF_ID': '000624649', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'William', 'LastName': 'Barbour', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'William Barbour', 'EmailAddress': '[email protected]', 'NSF_ID': '000827113', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ayan', 'LastName': 'Mukhopadhyay', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ayan Mukhopadhyay', 'EmailAddress': '[email protected]', 'NSF_ID': '000849812', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Meiyi', 'LastName': 'Ma', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Meiyi Ma', 'EmailAddress': '[email protected]', 'NSF_ID': '000873783', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Vanderbilt University', 'CityName': 'NASHVILLE', 'ZipCode': '372032416', 'PhoneNumber': '6153222631', 'StreetAddress': '110 21ST AVE S', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Tennessee', 'StateCode': 'TN', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'TN05', 'ORG_UEI_NUM': 'GTNBNWXJ12D5', 'ORG_LGL_BUS_NAME': 'VANDERBILT UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Vanderbilt University', 'CityName': 'NASHVILLE', 'StateCode': 'TN', 'ZipCode': '372032416', 'StreetAddress': '110 21ST AVE S', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Tennessee', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'TN05'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431246.xml'}
|
Vapor Deposited Polymers for High Energy Density Halide Ion Batteries
|
NSF
|
01/01/2025
|
12/31/2027
| 397,101 | 361,918 |
{'Value': 'Continuing Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Carole Read', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922418'}
|
Halide ion-based electrochemical charge storage systems are attracting immense attention due to their high theoretical energy densities, low flammability and low risk of metal dendrite formation, the promise of local component sourcing, and their unique utility as biocompatible power sources. Polymer-based electrodes and electrolytes have the potential to yield high energy density halide ion batteries, however these polymer materials are in their infancy, and design guidelines to create optimal materials are currently unknown. The goal of this project is to apply the polymer growth and vapor-processing advancements made in investigator's lab to develop competitive polymer electrodes and electrolytes for halide ion batteries. This work will produce experimentally validated guidelines for optimal polymer electrode and electrolyte materials that will broadly inform materials and device development endeavors in the electrochemical systems community. This project will provide education and training to graduate students engaged in Ph.D. research, undergraduates gaining their first research experiences, and community college students participating in an internship program that increases opportunities for minority and first-generation researchers in STEM fields.<br/> <br/>In their present iteration, polymer-based electrodes and electrolytes have not yet afforded sufficiently high chloride storage densities and conductivities, and design rules for accessing optimal materials have not been established. The overarching hypothesis of this effort is that the real-time composition, morphology and porosity control afforded by polymer chemical vapor deposition (CVD) will yield conductive polymer electrodes with a high volumetric density of accessible chloride-storage sites and halide-conducting gel/membrane electrolytes with high ionic conductivities. Different facets of this hypothesis are explored in each aim: (1) the advantage of using oxidative chemical vapor deposition (oCVD) to create thick and conductive chloride-storing electrodes with high volumetric chloride storage capacities is explored; (2) the ability of the photoinitiated chemical vapor deposition (piCVD) process to create gel and solid-membrane electrolytes with high chloride conductivity via controlled mesh sizes will be experimentally proven; (3) the compatibility of the reaction trajectories/deposition chemistries used in oCVD and piCVD with fluoride anion salts will be explored to develop materials for fluoride-ion batteries. The project plans span process research, and thin-film and electrochemical characterization efforts, complemented and accelerated by collaborative efforts to apply machine learning algorithms to predict competitive electrode structures.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/06/2024
|
08/06/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2431248
|
{'FirstName': 'Trisha', 'LastName': 'Andrew', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Trisha L Andrew', 'EmailAddress': '[email protected]', 'NSF_ID': '000733592', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Massachusetts Amherst', 'CityName': 'AMHERST', 'ZipCode': '010039252', 'PhoneNumber': '4135450698', 'StreetAddress': '101 COMMONWEALTH AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'MA02', 'ORG_UEI_NUM': 'VGJHK59NMPK9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MASSACHUSETTS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Massachusetts Amherst', 'CityName': 'AMHERST', 'StateCode': 'MA', 'ZipCode': '010039252', 'StreetAddress': '101 COMMONWEALTH AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'MA02'}
|
{'Code': '764400', 'Text': 'EchemS-Electrochemical Systems'}
|
2024~361918
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431248.xml'}
|
Conference: 2025 Micro and Nanoscale Phase Change Phenomena Gordon Research Conference and Seminar
|
NSF
|
10/01/2024
|
03/31/2025
| 25,000 | 25,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Shahab Shojaei-Zadeh', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928045'}
|
This award partially supports the 2025 Gordon Research Conference (GRC) and associated student-run Gordon Research Seminar (GRS) on Micro and Nanoscale Phase Change Phenomena to be held in Sheraton Fairplex Hotel & Conference Center, Pomona, California on January 11-17, 2025. As the fifth conference in the series, this GRC under the theme of Phase Change Phenomena in a Decarbonizing World will feature a diverse group of speakers and discussion leaders from institutions and organizations worldwide, with talks that concentrate on the latest developments in the field and define its most promising future directions. The goal is to present the latest in fundamental research, build the research community in the general area of micro and nanoscale phase change, inspire meaningful applications in decarbonization, and recommend on the most promising future research directions. The venue provides a unique forum where graduate students, postdoctoral associates and other junior researchers can interact informally with established members of the field. Early-career researchers will also be able to present their work, interact with each other, and participate in mentoring activities during the associated GRS, organized and run entirely by students and postdocs, as well as through poster presentations at the GRC. The GRC “Power Hour” is a forum designed to address challenges faced by women and all underrepresented groups in science and to discuss issues such as unconscious bias and overcoming barriers to inclusivity, as well as to provide mentoring to junior female scientists.<br/><br/>Processes involving phase change are critically important in a wide variety of electrification and decarbonization technologies. This GRC and associated GRS are focused on fundamental mechanisms governing phase change processes and how these mechanisms interact to prescribe how component technologies and systems can be designed and run in a decarbonizing world. Topics within the conference include processes occurring at the three-phase contact line, the thermodynamics and kinetics of phase change materials and thermochemical energy storage media, the design of materials and surfaces using advanced manufacturing techniques that can control phase change, advances in the simulation and numerical modeling of phase change processes, machine learning and artificial intelligence methods for characterizing and predicting phase change mechanisms, new and novel experimental methods for measuring the extent of phase change, and phase change processes occurring in novel refrigerant working fluids relevant to decarbonization. The 2025 GRC will bridge this gap between heat transfer experts and other scientists from important relevant disciplines. In addition, the significant time allotted for discussions within the GRC structure will foster collaborations amongst diverse researchers to rapidly accelerate understanding and provide a unified knowledge base. Early-career and established researchers in the field alike will be encouraged to participate in the talks and poster sessions, which will enhance their diversity and intellectual capacity. We anticipate that by fostering this multidisciplinary research community, the GRC will become the premier meeting in micro and nanoscale phase change processes.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2431261
|
[{'FirstName': 'Ying', 'LastName': 'Sun', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ying Sun', 'EmailAddress': '[email protected]', 'NSF_ID': '000388968', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Patricia', 'LastName': 'Weisensee', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Patricia B Weisensee', 'EmailAddress': '[email protected]', 'NSF_ID': '000755360', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Gordon Research Conferences', 'CityName': 'EAST GREENWICH', 'ZipCode': '028183454', 'PhoneNumber': '4017834011', 'StreetAddress': '5586 POST RD UNIT 2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Rhode Island', 'StateCode': 'RI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'RI02', 'ORG_UEI_NUM': 'XL5ANMKWN557', 'ORG_LGL_BUS_NAME': 'GORDON RESEARCH CONFERENCES', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Gordon Research Conferences', 'CityName': 'EAST GREENWICH', 'StateCode': 'RI', 'ZipCode': '028183454', 'StreetAddress': '5586 POST RD UNIT 2', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Rhode Island', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'RI02'}
|
{'Code': '140600', 'Text': 'TTP-Thermal Transport Process'}
|
2024~25000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431261.xml'}
|
CIVIC-PG Track B: Community-driven socio-technical infrastructure for data-driven air quality advocacy
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}
|
{'SignBlockName': 'Barbara Ransom', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927792'}
|
The American Lung Association stated that air quality, in particular that which contains large amount of particulate matter in urban settings, is a serious health problem for residents. In addition, for many parts of the U.S, government owned and maintained air monitoring equipment and data does not have the spatial resolution to provide communities, especially those in low income heavily polluted areas, with air quality data. This Civic Innovation Challenge (CIVIC) planning process brings together a science team with local community and civic organizations to co-design a science/research-based, implementable, scalable, and sustainable solution that addresses air quality, an important local community resilience problem in one of the Pittsburgh, low income, urban neighborhoods. This CIVIC planning activity supports infrastructure for the collection of local air quality data, a user-friendly platform that provides real or near real time data and its visualization and analysis. It also provides education and training of community members in advocacy that allow them to effectively work with local governments and other entities to improve air quality. The planning process will bring together all relevant stakeholders and community residents to co-design the low-cost air monitoring network and advocacy education and training regimen. Broader impacts include a community-based air monitoring network that will provide hyperlocal, real-time, air quality data to increase community education and awareness of air quality and its impacts on their health and lives and provide essential data to allow community advocacy for interventions and mitigation strategies thereby improving community health and well-being. <br/><br/>The project involves installation of low-cost air quality measurement and monitoring infrastructure to support a network of community scientists with online accessible tools to collect community air quality data, share individual and collective narratives about local environmental issues, and support the community in helping them know how to critically analyze data to build a science and data-driven advocacy campaign for improved community air quality. The project team will develop community training and education programs about air quality data, data analysis literacy, and how the data can be used for advocacy. Another objective is to design, with partners, and implement a community-engaged and participatory action approach to improving local air quality. An online data visualization platform will be developed to provide community members access to real-time air quality data that can be used to improve understanding, awareness of the impacts of compromised air quality to help individuals and the community advocate for action. This planning process will improve the understanding of how community-based efforts can be designed to lead to policy changes. It will also foster and strengthen collaboration between researchers and community stakeholders, develop new collaborations and partnerships, refine the research vision to enable submission of a successful follow-on proposal that will implement the community vision and provide data to address research questions and develop evaluation methods and measures for the follow-on project. Through this approach, the project team feels the activities and anticipated outcomes can be replicated in other similar urban communities facing similar challenges.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track B. Bridging the gap between essential resources and services & community needs and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy. The proposal is co-funded by the NSF Directorate for Geosciences and Directorate for Computer Information Science and Engineering.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/17/2024
|
08/17/2024
|
None
|
Grant
|
47.050, 47.070
|
1
|
4900
|
4900
|
2431262
|
[{'FirstName': 'Rosta', 'LastName': 'Farzan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rosta Farzan', 'EmailAddress': '[email protected]', 'NSF_ID': '000581618', 'StartDate': '08/17/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Erin', 'LastName': 'Walker', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Erin Walker', 'EmailAddress': '[email protected]', 'NSF_ID': '000604923', 'StartDate': '08/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Amy', 'LastName': 'Babay', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Amy E Babay', 'EmailAddress': '[email protected]', 'NSF_ID': '000811570', 'StartDate': '08/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Christina', 'LastName': 'Ndoh', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christina Ndoh', 'EmailAddress': '[email protected]', 'NSF_ID': '000949331', 'StartDate': '08/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Pittsburgh', 'CityName': 'PITTSBURGH', 'ZipCode': '152600001', 'PhoneNumber': '4126247400', 'StreetAddress': '4200 FIFTH AVENUE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'PA12', 'ORG_UEI_NUM': 'MKAGLD59JRL1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF PITTSBURGH - OF THE COMMONWEALTH SYSTEM OF HIGHER EDUCATION', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Pittsburgh', 'CityName': 'PITTSBURGH', 'StateCode': 'PA', 'ZipCode': '152600001', 'StreetAddress': '4200 FIFTH AVENUE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'PA12'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431262.xml'}
|
EAGER: Formal reasoning with SPIRAL program generation and automatic hardware-centric optimization to achieve guarantees in high performance math kernels produced by generative AI
|
NSF
|
10/01/2024
|
09/30/2025
| 295,169 | 295,169 |
{'Value': 'Standard Grant'}
|
{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}
|
{'SignBlockName': 'Almadena Chtchelkanova', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927498'}
|
In recent years, artificial intelligence (AI) has made major progress. Generative AI and, in particular, large language models (LLMs) have revolutionized how we think of AI. These methods are used broadly and are now also applied to program development. Before LLMs, human contributors, commenters and curators would ensure at least some minimum level of correctness when looking up such code fragments on programming-related internet sites. These guard rails are gone when using LLMs, as the system cannot provide any guarantees and insights to ensure the correctness of the produced examples. This LLM hallucination becomes a huge issue when LLMs are asked to provide examples for algorithms with complex and hard-to-understand behavior and where correctness is not obvious. In the worst-case scenario, generative AI provides incorrect and outdated code snippets from undocumented sources that are strung together into a “reasonably looking” example that may well be wrong in a subtle way, but only experts could spot the problem. Any effort that helps guard AI from acting outside its bounds and that ensures that one can trust in AI has a major scientific and societal impact. This project focuses on enabling trust when using AI as an aid to programmers. <br/><br/>This project develops an experimental approach to the above-described problem for a class of important core numerical algorithms. The team of researchers takes their inspiration from a well-understood insight in mathematics and computer science that proving a solution correct is easier than finding a solution. In the context of LLMs, they investigate how to utilize LLMs to guess an implementation of an algorithm, within clear implementation constraints. Then, they develop an extension to the SPIRAL system (www.spiral.net) that implements symbolic execution and theorem-proving capabilities to derive the semantics of the LLM-generated code using SPIRAL’s formal framework and engine. For the problems addressed by this project, the researchers aim to demonstrate how rule-based symbolic AI can bring guarantees to generative AI. While the problem of deriving the formal semantics of a piece of numerical code, in general, may well be unsolvable, for the class of algorithms that the SPIRAL system understands, the problem becomes tractable. The approach is a variant of lifting that leverages the detailed knowledge of numerical algorithms encoded in the rule-based AI components of the SPIRAL system.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/22/2024
|
07/22/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2431265
|
{'FirstName': 'Franz', 'LastName': 'Franchetti', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Franz Franchetti', 'EmailAddress': '[email protected]', 'NSF_ID': '000209896', 'StartDate': '07/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Carnegie-Mellon University', 'CityName': 'PITTSBURGH', 'ZipCode': '152133815', 'PhoneNumber': '4122688746', 'StreetAddress': '5000 FORBES AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'PA12', 'ORG_UEI_NUM': 'U3NKNFLNQ613', 'ORG_LGL_BUS_NAME': 'CARNEGIE MELLON UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'U3NKNFLNQ613'}
|
{'Name': 'Carnegie-Mellon University', 'CityName': 'PITTSBURGH', 'StateCode': 'PA', 'ZipCode': '152133890', 'StreetAddress': '5000 FORBES AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'PA12'}
|
{'Code': '779800', 'Text': 'Software & Hardware Foundation'}
|
2024~295169
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431265.xml'}
|
Conference: Advancing a Cultural Understanding of the Mexican Networks for inclusion into AccelNet GERI
|
NSF
|
07/01/2024
|
06/30/2025
| 49,610 | 49,610 |
{'Value': 'Standard Grant'}
|
{'Code': '01090000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OISE', 'LongName': 'Office Of Internatl Science &Engineering'}}
|
{'SignBlockName': 'Kara C. Hoover', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922235'}
|
We have embarked on building a global ecological Network-of-Networks (NoN), starting with six Environmental Research Infrastructures (ERIs) from around the world. This effort has come together under the Global Ecosystem Research Infrastructure (GERI) to tackle challenges in understanding the biosphere’s response to environmental changes, providing crucial information to researchers, managers, and decision-makers alike. We now seek to extend GERI to include networks and infrastructures from currently unrepresented regions and countries. As part of establishing a strong foundation in GERI, the founding networks have developed a robust cross-cultural understanding and social fabric within which they operate. GERI’s NoN roadmap, network activities, and scientific goals build upon this foundation. Since each network has its own cultural identity—including individual-to-national ways of working, perceptions, biases, strengths, science disciplines, challenges, and synergies—bringing new networks into GERI requires careful consideration of these diverse attributes and how they manifest in building a more inclusive and effective NoN. This workshop proposal is designed to assess the cultural framework and roadmap the inclusion of five Mexican networks into GERI. The workshop aims to (i) engender ownership and belonging among these networks within the GERI NoN, thereby facilitating an inclusive partnership; (ii) bring together early-career representatives from each network who will integrate GERI into their ongoing professional careers; and (iii) begin roadmapping an equitable process for the inclusion of new networks from underrepresented regions into GERI.<br/><br/>The Global Ecosystem Research Infrastructure (GERI) aims to enhance our understanding of and response to environmental changes affecting our planet. Our goal is to expand GERI by incorporating additional networks from regions and countries that have not yet been represented. The GERI network is built on a strong foundation of diverse cultural practices and scientific approaches from its founding members. As we integrate new networks, it’s crucial to consider their unique cultural identities and ways of working to enhance the network’s overall effectiveness. This specific workshop focuses on integrating five Mexican networks into GERI. The workshop aims to make these networks feel a part of GERI, helping them recognize the benefits and contributions they can bring to this international effort. We will also start to plan how to include more networks from other underrepresented regions fairly and effectively. The workshop will gather early-career professionals from these Mexican networks, who will use GERI throughout their careers, helping them to build their skills and understanding of global ecological challenges. It’s also an opportunity to learn from each other and apply these insights more broadly in future collaborations. In short, this workshop is not just about integrating these Mexican networks into GERI; it's about preparing the next generation of scientists to work collaboratively across borders and disciplines, fostering a diverse and inclusive global scientific community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
06/11/2024
|
06/11/2024
|
None
|
Grant
|
47.079
|
1
|
4900
|
4900
|
2431267
|
{'FirstName': 'Michael', 'LastName': 'SanClements', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michael SanClements', 'EmailAddress': '[email protected]', 'NSF_ID': '000644208', 'StartDate': '06/11/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Battelle Memorial Institute', 'CityName': 'COLUMBUS', 'ZipCode': '432012696', 'PhoneNumber': '6144244873', 'StreetAddress': '505 KING AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'OH03', 'ORG_UEI_NUM': 'F125YU6SWK59', 'ORG_LGL_BUS_NAME': 'BATTELLE MEMORIAL INSTITUTE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Battelle Memorial Institute', 'CityName': 'Columbus', 'StateCode': 'OH', 'ZipCode': '432012696', 'StreetAddress': '505 KING AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Ohio', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'OH03'}
|
{'Code': '069Y00', 'Text': 'AccelNet - Accelerating Resear'}
|
2024~49610
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431267.xml'}
|
CIVIC-PG Track A: Co-designing Toward Coastal Resilience: A Hybrid Approach for Restoring Hurricane and Climate Change-prone Seawalls and Dunes
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Siqian Shen', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927048'}
|
This Civic Innovation Challenge (CIVIC) Stage 1 project will fund research that attempts to address severe damage caused by hurricanes Ian and Nicole to Florida's Central East Coast in late 2022, which resulted in significant damage to Volusia County and rendered numerous beachfront properties uninhabitable. A strategic restoration plan will be developed that combines hard structures like seawalls with natural elements such as sand and vegetation, resulting in “living seawalls.” Such a restoration approach will enhance coastal resilience against future storms while promoting ecological and aesthetic benefits. By integrating natural and engineered solutions, the research will help stabilize dunes, protect habitats, and maintain beach access. This approach will balance environmental and economic needs, contributing to long-term community resilience. Furthermore, advanced climate modeling will be used in the design process to generate future storm scenarios, ensuring the effectiveness of these designs in the face of climate change. The research project will involve collaboration with local communities and stakeholders to develop a strategic plan that aligns with environmental policies, economic goals, and the coastal lifestyle. The anticipated results of this project include the development of a research agenda and evaluation metrics for a Stage 2 implementation. This project will advance the field by demonstrating the potential of hybrid coastal protection methods that take advantage of nature-based solutions. It will support education through community involvement, promotes diversity by engaging various stakeholders, and ultimately benefits society by enhancing coastal resilience, protecting property, and restoring natural habitats.<br/><br/>Stage 1 research will encompass community engagement workshops to consider, co-design, and adopt a research-based approach, schematics, and a location for the living seawall, potentially to be implemented in Stage 2 of the CIVIC solicitation. The workshop and potential implementation would focus on: a) adaptation of resilient natural foredunes, focusing on key ecological functions such as sand trapping, wind deflection, and habitat provision for species like sea turtles; b) design of the structural component which will integrate sophisticated climate modeling and stochastic simulations to assess performance under future climate scenarios; and c) consideration of socioeconomic and policy aspects involving stakeholders to co-design the seawalls, ensuring they meet ecological, aesthetic, and economic goals while adhering to environmental policies. The project will link ecosystem services such as property protection and recreation to community benefits and address permitting and insurance requirements. It will address structural endurance, ecological resilience, and socio-economic needs, providing guidelines for hybrid coastal restoration to bolster resilience against hurricanes amidst climate change. Measurable objectives include adopting a design aligned with regulations and securing shoreline properties for Stage 2 implementation and monitoring.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2431268
|
[{'FirstName': 'Stephen', 'LastName': 'Medeiros', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Stephen C Medeiros', 'EmailAddress': '[email protected]', 'NSF_ID': '000959762', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Hyun Jung', 'LastName': 'Cho', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hyun Jung Cho', 'EmailAddress': '[email protected]', 'NSF_ID': '000358627', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Siddharth', 'LastName': 'Parida', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Siddharth S Parida', 'EmailAddress': '[email protected]', 'NSF_ID': '000817469', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Kelly', 'LastName': 'San Antonio', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kelly M San Antonio', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A02F7', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Georgios', 'LastName': 'Apostolakis', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Georgios Apostolakis', 'EmailAddress': '[email protected]', 'NSF_ID': '000768254', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Embry-Riddle Aeronautical University', 'CityName': 'DAYTONA BEACH', 'ZipCode': '321143910', 'PhoneNumber': '3862267695', 'StreetAddress': '1 AEROSPACE BLVD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'FL06', 'ORG_UEI_NUM': 'U5MMBAC9XAM5', 'ORG_LGL_BUS_NAME': 'EMBRY-RIDDLE AERONAUTICAL UNIVERSITY, INC.', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Embry-Riddle Aeronautical University', 'CityName': 'DAYTONA BEACH', 'StateCode': 'FL', 'ZipCode': '321143910', 'StreetAddress': '1 AEROSPACE BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'FL06'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431268.xml'}
|
CRII: CNS: Integrated Sensing and Communication with Optical Wireless: A Retro-reflective Link Design
|
NSF
|
08/15/2024
|
09/30/2025
| 174,999 | 172,848 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Alhussein Abouzeid', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032920000'}
|
Integrated sensing and communication with optical wireless (ISAC-OW) is a potential 6G enabling technology. Leveraging visible light and infrared spectrums, high-precision sensing and positioning, and high-speed mobile communication can be realized in a single system, enabling advanced solutions for future 6G scenarios, such as smart hospitals and industrial automation. The retro-reflective optical uplink is a promising emerging solution to ISAC-OW that offers several favorable features including hassle-free alignment, minimal interference to adjacent links, microwatt power consumption, low hardware complexity, glaring-free and sniff-proof, and enables simultaneous sensing, positioning and communication with a compact-size tag under a single luminaire. However, the potential of retro-reflective link-based ISAC-OW technology is tempered by basic theoretical and technology development challenges that require a cross-disciplinary approach. The project will investigate fundamental design trade-offs in a retro-reflective uplink enabled ISAC-OW system for large-scale networks. The expected project results advance the state-of-the-art of basic theory and practical design strategies for ISAC-OW system. The project provides cross-disciplinary training opportunities for under-represented students spanning communication theory and signal processing, optical wireless system and circuit design, and wireless networking.<br/><br/>The proposed research develops a new cross-domain framework for integrated design of efficient and scalable retro-reflective uplink enabled ISAC-OW networks. The project is anchored on four key research goals: 1) Modeling the retro-reflective optical link and investigating the hardware design of light reader and retro-reflective tag to convey as much luminous flux as possible from the emitter to the receiver; 2) Investigation of MAC protocols to fully exploit the physical (PHY) layer capabilities and address concurrent transmission challenges; 3) Development of an efficient and flexible spectrum allocation strategy for joint sensing and communication; and 4) Integrated system modeling and assessment for performance-complexity-energy optimization and testbed-based experimental validation of hardware and protocols. The proposed research features investigation of several key operational requirements, including analytical optical models of ISAC-OW, dynamic hardware reconfigurability and scalability, concurrent transmission mechanism and new spectrum allocation methods for ISAC in different use cases. The proposed research acts as a catalyst for cross-disciplinary design and analysis of emerging ISAC-OW system in industry and academia to meet the connected intelligence and application requirements.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
05/06/2024
|
05/06/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2431272
|
{'FirstName': 'Sihua', 'LastName': 'Shao', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sihua Shao', 'EmailAddress': '[email protected]', 'NSF_ID': '000813635', 'StartDate': '05/06/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Colorado School of Mines', 'CityName': 'GOLDEN', 'ZipCode': '804011887', 'PhoneNumber': '3032733000', 'StreetAddress': '1500 ILLINOIS ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Colorado', 'StateCode': 'CO', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'CO07', 'ORG_UEI_NUM': 'JW2NGMP4NMA3', 'ORG_LGL_BUS_NAME': 'TRUSTEES OF THE COLORADO SCHOOL OF MINES', 'ORG_PRNT_UEI_NUM': 'JW2NGMP4NMA3'}
|
{'Name': 'Colorado School of Mines', 'CityName': 'GOLDEN', 'StateCode': 'CO', 'ZipCode': '804011887', 'StreetAddress': '1500 ILLINOIS ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Colorado', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'CO07'}
|
{'Code': '736300', 'Text': 'Networking Technology and Syst'}
|
2023~172848
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431272.xml'}
|
CIVIC-PG Track B: Strengthening Community Safety and Well-being with Ethical, AI-Assisted Video Solutions
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'David Corman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928754'}
|
The research-centered CIVIC pilot aims to bring recent advances in Artificial Intelligence (AI) and video analytics to transform Charlotte's city center from a traditional Central Business District (CBD) space into a dynamic Central Activity District (CAD). To this end, this project will leverage privacy-preserving video analytics with integrated AI-assisted solutions to influence public perception and usage of urban spaces, enhancing the urban living experience, improving the quality of life, and reducing service disruptions. More specifically, the proposed pilots aim to (1) create proactive safety measures to enhance safety and perception of safety in uptown Charlotte; (2) address critical information gaps in understanding complex micro walking behaviors and dynamics of pedestrian flows for more efficient and intentional resource allocation; (3) and enable meaningful AI-guided soft changes in city center infrastructure. This planning phase includes a unique, established partnership between UNC Charlotte and Charlotte Center City Partners (CCCP), a leading civic organization, and other diverse stakeholders. The team will also work to get feedback from local businesses, residential communities, and other civic partners, such as local government and private service providers, as well as the larger general public of Charlotte. <br/><br/>The proposed pilot aims to redefine the role of Closed Circuit Television (CCTV) cameras from passive surveillance devices to insightful, proactive tools providing actionable insights to stakeholders and civic organizations by leveraging recent breakthroughs in privacy-preserving AI and real-time edge video analytics. This project's research and planning activities are centered around transforming existing passive surveillance devices into insightful tools for community and economic development that can deliver continuous growth, prosperity, and inclusion in cities. The pilot aims to break the barriers in translational research and pave the way for the responsible deployment of AI technologies within the city environment at a large scale, combining technical innovation with social, ethical, and legal aspects for responsible deployment. At the same time, this project establishes a robust community-in-the-loop framework that ensures that insights derived from AI analytics are directly fed back to the community, thus fostering a collaborative ecosystem where real-time data and community feedback inform decisions<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track B. Bridging the gap between essential resources and services & community needs and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/26/2024
|
07/26/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2431274
|
[{'FirstName': 'Shannon', 'LastName': 'Reid', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shannon Reid', 'EmailAddress': '[email protected]', 'NSF_ID': '000740241', 'StartDate': '07/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Hamed', 'LastName': 'Tabkhi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hamed Tabkhi', 'EmailAddress': '[email protected]', 'NSF_ID': '000719441', 'StartDate': '07/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Philip', 'LastName': 'Otienoburu', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Philip E Otienoburu', 'EmailAddress': '[email protected]', 'NSF_ID': '000630838', 'StartDate': '07/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of North Carolina at Charlotte', 'CityName': 'CHARLOTTE', 'ZipCode': '282230001', 'PhoneNumber': '7046871888', 'StreetAddress': '9201 UNIVERSITY CITY BLVD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NC12', 'ORG_UEI_NUM': 'JB33DT84JNA5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF NORTH CAROLINA AT CHARLOTTE, THE', 'ORG_PRNT_UEI_NUM': 'N8DMK1K4C2K5'}
|
{'Name': 'University of North Carolina at Charlotte', 'CityName': 'CHARLOTTE', 'StateCode': 'NC', 'ZipCode': '282230001', 'StreetAddress': '9201 UNIVERSITY CITY BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'NC12'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431274.xml'}
|
Planning: Center for Renewable Energy and Biotechnology (CREB)
|
NSF
|
09/15/2024
|
08/31/2026
| 199,994 | 199,994 |
{'Value': 'Standard Grant'}
|
{'Code': '03090000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'CHE', 'LongName': 'Division Of Chemistry'}}
|
{'SignBlockName': 'Anne-Marie Schmoltner', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924716'}
|
This CREST-CHE planning award is funded jointly by the Division of Chemistry and the Division of Equity for Excellence in STEM and supports Professors Shahidul Islam, Robert Marsteller, and their team to plan for the establishment of the Center for Renewable Energy and Biotechnology (CREB) at Delaware State University (DSU), a Historically Black College and University (HBCU). The planned CREB center will bring together scientists to create new materials and technologies, such as improved solar panels, batteries and biofuel. These advancements are important because they offer cleaner and more sustainable alternatives to traditional energy sources like coal and oil, which can harm the environment. The project also aims to involve students, particularly those from underrepresented backgrounds, providing them with valuable experience and skills in science and technology and support their educational pathways.<br/><br/>The CREB center will develop cost-effective polymers for optoelectronic applications and nanoporous high-entropy cathodes for sodium-ion batteries, providing an eco-friendly alternative to lithium-ion batteries. The center will also explore biodiesel production, offering a sustainable option over fossil fuels. The planning grant will support the identification of existing assets, the establishment of collaborative research teams, and the creation of an organizational framework for governance and evaluation. A Steering Committee and Advisory Committees will guide the planning process, while subcommittees will address critical areas such as infrastructure and partnerships. The project involves an interdisciplinary team of experts, including those in polymer chemistry, nanotechnology, biochemistry, computational chemistry, and data science. This initiative will not only enhance DSU's research capabilities but also provide students with hands-on experience in cutting-edge scientific research, aligning with industry demands and supporting the growth of DSU's Applied Chemistry PhD program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/27/2024
|
08/27/2024
|
None
|
Grant
|
47.049, 47.076
|
1
|
4900
|
4900
|
2431276
|
[{'FirstName': 'Robert', 'LastName': 'Marsteller', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robert B Marsteller', 'EmailAddress': '[email protected]', 'NSF_ID': '000895361', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Shahidul', 'LastName': 'Islam', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shahidul Islam', 'EmailAddress': '[email protected]', 'NSF_ID': '000843683', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Delaware State University', 'CityName': 'DOVER', 'ZipCode': '199012202', 'PhoneNumber': '3028576001', 'StreetAddress': '1200 N DUPONT HWY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Delaware', 'StateCode': 'DE', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'DE00', 'ORG_UEI_NUM': 'RZZ8BMQ47KX3', 'ORG_LGL_BUS_NAME': 'DELAWARE STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Delaware State University', 'CityName': 'DOVER', 'StateCode': 'DE', 'ZipCode': '199012202', 'StreetAddress': '1200 N DUPONT HWY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Delaware', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'DE00'}
|
[{'Code': '748700', 'Text': 'BROADENING PARTICIPATION'}, {'Code': '913100', 'Text': 'Centers for Rsch Excell in S&T'}]
|
2024~199994
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431276.xml'}
|
CIVIC-PG Track A: Incorporating large-area imaging and analytics into community-driven underwater restoration and management
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}
|
{'SignBlockName': 'Barbara Ransom', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927792'}
|
As the climate changes, coastal communities are putting greater value on the ability of nearshore marine ecosystems to dissipate storm surges and protect human infrastructure and livelihoods. Thus, coastal ecosystem stewardship and restoration is increasingly viewed as a smart ecologic and economic investment in “green” infrastructure. This Civic Innovation Challenge (CIVIC) planning process brings together university scientists, community representatives and businesses, and civic entities to co-design a science/research-based, implementable, scalable, and sustainable solution that tackles a critical challenge: Coral reef degradation and destruction due to climate change. This is a challenge that needs to be addressed to increase island and tropical community resilience and protection from sea level rise and erosion caused by increased storm frequency and intensity. This project, and its planning team, work to address the coastal protection problem by employing advanced technology for the monitoring and restoration of coral reefs using the U.S. Virgin Islands as a pilot. For island communities, like those in the Virgin islands, coral reefs are the natural and premier frontline barrier that mitigates onshore destruction of harbor installations, homes, businesses, and other installed infrastructure from damaging wave action and storm surges. For this CIVIC planning process the science team from the Scripps Institution of Oceanography brings new technology (large-area imaging) to the table, working with the community-based U.S. Virgin Island Restoration of Coral Squad, to co-create an implementation plan for deploying an innovative coral reef monitoring and technology training regimen to keep track of local coral reef degradation and monitor the effectiveness of community reef restoration efforts. Civic partners engaged in this effort include local businesses, non-profits, and government agencies who want to work with academic partners who have expertise in techniques that can help them in their fight to maintain health coral reefs around their islands. Together, the scientists and community are co-designing with what could be an effective model for community-university exchange, scalability, and sustainability for community use of new technology (i.e., large-area imaging) and utilizing its benefits for improving coastal community resilience. Broader impacts of the work include deployment of a novel technology to enable more informed means of monitoring and checking the health of coral reefs and efforts to maintain them in a warming ocean world and training of local residents and civic partners in the use and utility of the technology and working closely with university scientists. The work will also engage students from the U.S. Virgin Islands. <br/><br/>The project involves the use of a technology new to ocean science: Large-area imaging technology (a.k.a. photogrammetry). It can enhance and accelerate coastal restoration by creating a visual “digital twin” that can be used to gauge the relative success of reef degradation and the effectiveness of different restoration approaches. This CIVIC planning process brings together a network of scientists, a novel technology, and accessible online tools and image processing techniques to help island communities, like those in the US Virgin Islands, better monitor fringing coral reef health. The value of large-area imaging is that it provides a visual understanding of the results of outcomes of the interaction between rising ocean temperature and coral reef ecosystem health. While this technology offers immense potential, financial and technical limitations have prevent widespread uptake outside of academic circles. Surveys of individuals working in marine ecosystem stewardship and restoration have documented systemic inequities in access to emerging technologies such as large-area imaging. These challenges are linked, in some cases, to financial constraints; but many are linked to uneven investment in user training and in access to the technology and technology-enabled workflows. The goal of this collaboration and planning process is to have scientists and end-user stakeholders identify impediments to access in the context of coral restoration in the US Virgin Islands. A multi-stakeholder meeting in the US Virgin Islands will provide community-wide perspectives that will help in the co-design of potential solutions. This will result in access to advanced technology and training in its use to accelerate the learning and technology implementation needed to build more climate-ready marine ecosystems. This planning process will improve the understanding how community-based efforts can be designed to provide improved nature-based solutions to climate change. It will also foster and strengthen collaboration between researchers and community stakeholders, develop new collaborations and partnerships, refine the research vision to enable submission of a successful follow-on proposal that will implement the community vision, and provide data to address research questions and develop evaluation methods and measures for the follow-on project.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy. The project was funded by the NSF Director for Geosciences.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.050
|
1
|
4900
|
4900
|
2431301
|
{'FirstName': 'Stuart', 'LastName': 'Sandin', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Stuart A Sandin', 'EmailAddress': '[email protected]', 'NSF_ID': '000076935', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-San Diego Scripps Inst of Oceanography', 'CityName': 'LA JOLLA', 'ZipCode': '920931500', 'PhoneNumber': '8585341293', 'StreetAddress': '8622 DISCOVERY WAY # 116', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_ORG': 'CA50', 'ORG_UEI_NUM': 'QJ8HMDK7MRM3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA SAN DIEGO', 'ORG_PRNT_UEI_NUM': 'QJ8HMDK7MRM3'}
|
{'Name': 'University of California-San Diego Scripps Inst of Oceanography', 'CityName': 'LA JOLLA', 'StateCode': 'CA', 'ZipCode': '920931500', 'StreetAddress': '8622 DISCOVERY WAY # 116', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_PERF': 'CA50'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431301.xml'}
|
CIVIC-PG Track B: Revitalizing Existing Community Infrastructure for Affordable and Efficient Passenger Rail Mobility Solutions
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Siqian Shen', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927048'}
|
This Civic Innovation Challenge (CIVIC) Stage 1 project will support research that intends to develop and provide a roadmap for revitalizing legacy rail lines—which are abandoned, out-of-service, or underutilized railroad tracks. There are thousands of miles of existing but underused legacy lines in urban and rural communities across the country. This existing infrastructure is poised to improve accessibility by better connecting underserved communities to essential services. The primary barrier to using legacy rail lines is the lack of affordable rail-defect detection systems, which are important safety mechanisms. This research project aims to overcome that barrier. The project team — academic, civic, community, and industry partners — will use Philadelphia’s Delaware River waterfront as a demonstration site using a low-cost, artificial intelligence-based technology previously developed by the team. This technology, which is installed onboard trains, detects broken rails and other track damage in near real-time, facilitating a transition of a legacy line to active passenger rail in months rather than years. Research completed in association with project is the culmination of a decade-long process of public engagement and research, identifying rail as the preferred choice for improving accessibility because it better connects with other transit modes, supports high-capacity needs, stimulates local economies, adapts to increasing demand, offers more reliable service, and produces fewer emissions per passenger than cars and buses. By repurposing dormant rail assets, the project aims to enhance connectivity, reduce traffic congestion, promote environmentally friendly transportation, revitalize communities, and improve living standards in both urban and rural settings.<br/><br/>To achieve these goals, the research will strive to reintroduce affordable, dynamic, and community-driven legacy rail systems by transitioning new, safe technologies into an industry traditionally adverse to rapid change. The onboard monitoring and detection technology deployed and tested through this project combines two complementary sensing modalities: real-time acceleration data to inform statistical anomaly detection algorithms and real-time automated computer vision for detecting broken rails and classifying track damage. This adaptable system provides actionable data on integrity and ridership, reducing the time and financial barriers compared to traditional rail upgrades, and facilitating quicker regulatory approval and community acceptance. In Stage 1, this research project will: (1) integrate this technology within passenger rail intending to demonstrate that it is adaptable to various types of trains and locations, (2) assess the economic impacts of revitalized legacy rail, (3) gain community feedback on implementation needs, and (4) address the regulatory, financial, and governance implications of deploying advanced technologies for revitalizing legacy rail infrastructure. <br/><br/>This project is in response to the Civic Innovation Challenge program’s Track B. Bridging the gap between essential resources and services & community needs and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2431309
|
[{'FirstName': 'Mario', 'LastName': 'Berges', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mario E Berges', 'EmailAddress': '[email protected]', 'NSF_ID': '000588353', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Katherine', 'LastName': 'Flanigan', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Katherine A Flanigan', 'EmailAddress': '[email protected]', 'NSF_ID': '000841959', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Carnegie-Mellon University', 'CityName': 'PITTSBURGH', 'ZipCode': '152133815', 'PhoneNumber': '4122688746', 'StreetAddress': '5000 FORBES AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'PA12', 'ORG_UEI_NUM': 'U3NKNFLNQ613', 'ORG_LGL_BUS_NAME': 'CARNEGIE MELLON UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'U3NKNFLNQ613'}
|
{'Name': 'Carnegie-Mellon University', 'CityName': 'PITTSBURGH', 'StateCode': 'PA', 'ZipCode': '152133815', 'StreetAddress': '5000 FORBES AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'PA12'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431309.xml'}
|
CIVIC-PG Track A: Disaster Response Metaverse (DRM) for Enhancing Community Engagement through Immersive, Interactive Experiences
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Daan Liang', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922441'}
|
The objective of this Civic Innovation Challenge (CIVIC) Disaster Response Metaverse (DRM) project is to support research on developing an innovative, immersive virtual reality platform for disaster response training. The research intends to bridge the gap between fundamental knowledge and practical experience in emergencies, particularly for communities at risk of tornadoes or flooding. The DRM works to enable first responders, local officials, and community members to engage in more realistic disaster simulations to improve preparedness, decision-making, and collaboration. By leveraging cutting-edge technology to create accessible, scalable solutions, the DRM will align with broader public safety and sustainable development goals. The research advances the understanding of effective disaster response strategies and explore how immersive technologies could transform education and training across multiple fields and applications.<br/><br/>The DRM research project employs a multidisciplinary approach, combining expertise in engineering, computer science, emergency management, and social sciences. The research has two key dimensions: technical development and social impact analysis. Technical development centers on optimization of immersive features to replicate real-world disaster scenarios and ensure equitable access across diverse user groups. Social impact analysis examines how participation in the metaverse influences community cohesion, trust-building, and engagement in disaster preparedness. Stage 1 activities focus on refining the DRM platform, forming interdisciplinary teams, and developing detailed research protocols. In Stage 2, the DRM is deployed in community settings, conducting pilot studies, and analyzing user interactions and learning outcomes. The project team co-creates DRM centers where civic member freely accesses the virtual platform.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2431326
|
[{'FirstName': 'Jisoo', 'LastName': 'Park', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jisoo Park', 'EmailAddress': '[email protected]', 'NSF_ID': '000917580', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Inbae', 'LastName': 'Jeong', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Inbae Jeong', 'EmailAddress': '[email protected]', 'NSF_ID': '000849959', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Youjin', 'LastName': 'Jang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Youjin Jang', 'EmailAddress': '[email protected]', 'NSF_ID': '000855485', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Indiana State University', 'CityName': 'TERRE HAUTE', 'ZipCode': '478091902', 'PhoneNumber': '8122373088', 'StreetAddress': '200 N 7TH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Indiana', 'StateCode': 'IN', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_ORG': 'IN08', 'ORG_UEI_NUM': 'WBLRF8Z4BEF6', 'ORG_LGL_BUS_NAME': 'INDIANA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'WBLRF8Z4BEF6'}
|
{'Name': 'Indiana State University', 'CityName': 'TERRE HAUTE', 'StateCode': 'IN', 'ZipCode': '478091902', 'StreetAddress': '200 N 7TH ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Indiana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_PERF': 'IN08'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431326.xml'}
|
CIVIC-PG Track A: Machine Learning Approaches to Improve Resilience of Water Utilities to Extreme Weather Events
|
NSF
|
10/01/2024
|
03/31/2025
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Daan Liang', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922441'}
|
The objective of this Civic Innovation Challenge (CIVIC) project is to support research on design and implementation of a machine learning (ML)-based system, called WAUTO (Water operations AUTOmation), to optimize wastewater treatment plant operations during extreme weather events. Working with the Little Patuxent Wastewater Reclamation Plant (LPWRP), researchers from the Johns Hopkins University Applied Physics Laboratory (APL) and the Whiting School of Engineering (WSE) aim to enhance LPWRP’s resilience to extreme weather. Climate change is resulting in more frequent floods with higher water levels than what current models predict. In Howard County, MD, two floods, each expected to occur only every 1,000 years, took place within two years. The challenges faced by LPWRP are common nationwide. Smaller facilities, usually serving economically disadvantaged and marginalized communities, are especially vulnerable to flooding events. The WAUTO intends to enable continued system operation essential to public health and prosperity throughout the disaster. A wide range of stakeholders are engaged, including engineers, plant managers, and government officials. Success of this project could pave the way for the deployment of cutting-edge ML-based solutions for protecting critical infrastructures of national importance. <br/><br/>In this project, the researchers build a high accuracy model to predict the inflow and plant capacity as well as a model of plant equipment. Using features such as the water table / river levels and weather for the first model, and schematics/documentation and subject matter expertise for the second, the team trains a Reinforcement Learning (RL) agent to optimize plant operations by taking actions such as adjusting water flow rates and equalizing tank levels, based on predictions from the models as well real-time observations. For the Stage 2 Pilot, WAUTO will deployed at LPWRP through a phased approach as confidence in its performance improves. This civic-academic team consists of professionals from LPWRP, the Howard County Department of Public Works (DPW), researchers from APL and WSE, experts in geology and weather, and members from the broader community.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2431342
|
[{'FirstName': 'Tamim', 'LastName': 'Sookoor', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tamim Sookoor', 'EmailAddress': '[email protected]', 'NSF_ID': '000852143', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Yinzhi', 'LastName': 'Cao', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yinzhi Cao', 'EmailAddress': '[email protected]', 'NSF_ID': '000689464', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Johns Hopkins University', 'CityName': 'BALTIMORE', 'ZipCode': '212182608', 'PhoneNumber': '4439971898', 'StreetAddress': '3400 N CHARLES ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MD07', 'ORG_UEI_NUM': 'FTMTDMBR29C7', 'ORG_LGL_BUS_NAME': 'THE JOHNS HOPKINS UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Johns Hopkins University Applied Physics Laboratory', 'CityName': 'Laurel', 'StateCode': 'MD', 'ZipCode': '207236099', 'StreetAddress': '11100 Johns Hopkins Road', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'MD03'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431342.xml'}
|
CIVIC-PG Track A: Accelerating Coproduced Flood Resilience in Underserved Levee Communities
|
NSF
|
10/01/2024
|
03/31/2025
| 74,996 | 74,996 |
{'Value': 'Standard Grant'}
|
{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}
|
{'SignBlockName': 'Barbara Ransom', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927792'}
|
Flooding is an increasingly prevalent, dangerous, and costly phenomenon being driven by climate change and its related incidence of events that involve extreme precipitation. Protection from flooding, especially for rural and small communities, depends on levees put up and maintained by local authorities. Many of these are not accredited by FEMA due to complications in the accreditation process and lack of the means and knowledge of local communities on how to evaluate levee integrity. Unaccredited levee systems saddle communities with high flood insurance rates and could result in potential danger to communities and the surrounding area from inadequate levee management and/or construction. This Civic Innovation Challenge (CIVIC) planning process uses rural areas in Pennsylvania as a pilot to bring scientists and rural/small communities that own levees together with engineering firms, levee evaluation experts, and state and regional stakeholder entities to co-design tools and a process that provides improved flood resilience and levee safety and management for rural communities. A goal of the project is also to help communities with unaccredited levees navigate the accreditation process. Planned deliverables include the piloting of cutting-edge, low-cost, non-invasive geophysical and geospatial testing for levee monitoring and evaluation; leveraging high-resolution flood modeling capabilities to quickly generate risk-based flood and levee indicators to inform preliminary accreditation decision; and identifying practices that can be implemented across rural communities to improve levee safety. The planning process involves co-design with stakeholders to refine the vision and co-design a process for fast-paced engagement with levee regulators leading to levee accreditation, delivering tools for better community levee management and evaluation of levee integrity, and introducing and incorporating innovations in levee monitoring and construction. Refinement of the vision and co-design of possible solutions include a multi-disciplinary science team and the Office of Government and Public Relations from Penn State, engineers and levee inspection professionals from Pennsylvania engineering firms, the Pennsylvania State Department of Environmental Protection, and community representatives from the Pennsylvania Boroughs of Evertt; Patton; and Philipsbury; and Smithfield Township. Representatives from FEMA and the Susquehanna River Basin Commission will also be involved. Broader impacts include development of online tools and accessible data analysis and visualization products to help rural communities monitor and safely manage their levee systems. It also provides information needed to ensure local levees are safe and can control climate-driven flooding, potentially leading to levee accreditation and reduced flood insurance costs. <br/><br/>The goal of this CIVIC planning period is to bring together key stakeholders from across Pennsylvania and from the levee regulatory/accreditation sector to co-design methods and the elements, applications, user interfaces, and visualizations using low-cost, non-invasive satellite/geospatial and geophysical techniques to improve the safety and integrity of non-governmentally operated small community and rural unaccredited levee systems. The activity involves planning for the creation of a digital, levee, diagnostic tool and a story-map-based community guide for levee maintenance, evaluation and accreditation. The tool will allow users to examine existing levees in Pennsylvania and explore the associated levee data and indicators, such as risk of overtopping, projected cost of accreditation, cost of insurance premiums if accredited, etc. It will also describe the testing, modeling and community engagement activities for each community partner so other communities can better understand accreditation criteria, technology, engineering innovations, and cost-saving options. The tool will use the Google Cloud Platform, Python Dash, and geographic information systems (GIS) hosted online for free by Penn State Cloud Services. This planning process and the engaged group of stakeholders will work together to provide community access to high-resolution, remote sensing, geospatial, and geophysical and information that will allow improved monitoring, safety, and management of local levee systems as well as a path to levee accreditation. This planning process is designed to improve the understanding of how collaboration between communities and government entities can solve problems impacting small and rural communities impacted by flooding brought on by climate change. It will foster and strengthen collaboration between researchers, community stakeholders, and regulators, develop new collaborations and partnerships, refine the research vision to enable submission of a successful follow-on proposal that will implement the project vision and provide information to address research questions and develop evaluation methods and measures for the follow-on project. <br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy. The grant was co-funded by the NSF Directorate for Geosciences and the Directorate for Engineering.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/28/2024
|
08/28/2024
|
None
|
Grant
|
47.041, 47.050
|
1
|
4900
|
4900
|
2431345
|
[{'FirstName': 'Christine', 'LastName': 'Kirchhoff', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christine J Kirchhoff', 'EmailAddress': '[email protected]', 'NSF_ID': '000498895', 'StartDate': '08/28/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Alfonso', 'LastName': 'Mejia', 'PI_MID_INIT': 'I', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Alfonso I Mejia', 'EmailAddress': '[email protected]', 'NSF_ID': '000646702', 'StartDate': '08/28/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Kaleigh', 'LastName': 'Yost', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kaleigh Yost', 'EmailAddress': '[email protected]', 'NSF_ID': '000935082', 'StartDate': '08/28/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Pennsylvania State Univ University Park', 'CityName': 'UNIVERSITY PARK', 'ZipCode': '168021503', 'PhoneNumber': '8148651372', 'StreetAddress': '201 OLD MAIN', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '15', 'CONGRESS_DISTRICT_ORG': 'PA15', 'ORG_UEI_NUM': 'NPM2J7MSCF61', 'ORG_LGL_BUS_NAME': 'THE PENNSYLVANIA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Pennsylvania State Univ University Park', 'CityName': 'UNIVERSITY PARK', 'StateCode': 'PA', 'ZipCode': '168021503', 'StreetAddress': '201 OLD MAIN', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '15', 'CONGRESS_DISTRICT_PERF': 'PA15'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~74996
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431345.xml'}
|
AGS-CIF: Doppler On Wheels Network and Ruggedized Array of Pods/Poles (DOWNET)
|
NSF
|
09/01/2024
|
08/31/2028
| 1,151,915 | 448,486 |
{'Value': 'Cooperative Agreement'}
|
{'Code': '06020300', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'AGS', 'LongName': 'Div Atmospheric & Geospace Sciences'}}
|
{'SignBlockName': 'Nicholas Anderson', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924715'}
|
The Division of Atmospheric and Geospace Sciences (AGS) operates the Community Instruments and Facilities (CIF) program to enhance the scientific community’s access to instrumentation that is otherwise too costly or complicated to operate for most institutions. This award is for two Doppler on Wheels mobile radars and an array of surface weather stations, known as DOWNET. Mobile Doppler radars are used to study a variety of societally-impactful topics, from tornadoes to snowfall. The DOWNET instruments will also be used to teach younger generations through outreach events and hands-on training.<br/><br/>The DOWNET facility consists of two mobile, dual-polarization, dual-frequency, Doppler X-band radars and an array of surface- and pole-based deployable weather stations. The DOWNET facility is available for studies of severe and high impact weather, convective initiation, storm transitions and upscale growth, winter storms, orographic precipitation, precipitation microphysics, hydrological processes, tornado and hurricane structure, weather modification validation/refutation, fire weather, land use impacts, and more. DOWNET can be used in mobile or fixed mode. DOWNET is also available for outreach and/or educational purposes.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/07/2024
|
08/07/2024
|
None
|
CoopAgrmnt
|
47.050
|
1
|
4900
|
4900
|
2431370
|
{'FirstName': 'Karen', 'LastName': 'Kosiba', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Karen A Kosiba', 'EmailAddress': '[email protected]', 'NSF_ID': '000316164', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Illinois at Urbana-Champaign', 'CityName': 'URBANA', 'ZipCode': '618013620', 'PhoneNumber': '2173332187', 'StreetAddress': '506 S WRIGHT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'IL13', 'ORG_UEI_NUM': 'Y8CWNJRCNN91', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ILLINOIS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Illinois at Urbana-Champaign', 'CityName': 'URBANA', 'StateCode': 'IL', 'ZipCode': '618013620', 'StreetAddress': '506 S WRIGHT ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_PERF': 'IL13'}
|
{'Code': '152900', 'Text': 'FARE-Facil for Atmos Res & Ed'}
|
2024~448486
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2431370.xml'}
|
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