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Collaborative Research: DASI Track 1--AUtonomous Remote geospace Observation and Research Array (AURORA)
|
NSF
|
09/01/2024
|
08/31/2028
| 1,632,000 | 470,017 |
{'Value': 'Continuing Grant'}
|
{'Code': '06020000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'AGS', 'LongName': 'Div Atmospheric & Geospace Sciences'}}
|
{'SignBlockName': 'Roman Makarevich', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927207'}
|
High-latitude and polar regions present a unique set of challenges for continuous observations because of their remoteness and extreme and harsh environments. This project seeks to develop the next generation of small, low-power, autonomous, multi-instrument adaptive, ground-based geospace observation arrays, named AUtonomous Remote Geospace Observation and Research Array (AURORA). It is designed to fill large gaps in the currently existing ground-based instrument arrays in the high-latitude and polar regions. <br/><br/>With advanced technologies in solar panels, batteries, bidirectional satellite communication, low-power sensors (fluxgate and searchcoil magnetometers, radio receivers, etc.), and high-performance single-board computers, AURORA will enable year-round observations with cost-effective, multiple instruments in these remote logistically challenging locations. This will significantly improve the ability to study (1) interhemispheric asymmetries from the viewpoint of geomagnetic and ionospheric variability, (2) the mesoscale of solar-wind - magnetosphere - ionosphere coupling in high-latitude and polar regions, as well as other space weather phenomena. Deep-field autonomous observatories have the potential to co-locate instruments across disciplines in polar science and facilitate international collaborations. This project will also contribute to training the future workforce. It will support two early-career researchers including a female early-career scientist. Graduate and undergraduate students will participate in the research, assisting with instrumentation design and testing.<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.
|
07/15/2024
|
07/15/2024
|
None
|
Grant
|
47.050
|
1
|
4900
|
4900
|
2432886
|
[{'FirstName': 'Zhonghua', 'LastName': 'Xu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zhonghua Xu', 'EmailAddress': '[email protected]', 'NSF_ID': '000661074', 'StartDate': '07/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Shane', 'LastName': 'Coyle', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shane E Coyle', 'EmailAddress': '[email protected]', 'NSF_ID': '000927255', 'StartDate': '07/15/2024', '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': 'X6KEFGLHSJX7'}
|
{'Name': 'Virginia Polytechnic Institute and State University', 'CityName': 'BLACKSBURG', 'StateCode': 'VA', 'ZipCode': '240603359', 'StreetAddress': '300 TURNER ST NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'VA09'}
|
{'Code': '420200', 'Text': 'Upper Atmospheric Facilities'}
|
2024~470017
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2432886.xml'}
|
Collaborative Research: DASI Track 1--AUtonomous Remote geospace Observation and Research Array (AURORA)
|
NSF
|
09/01/2024
|
08/31/2028
| 358,690 | 20,000 |
{'Value': 'Continuing Grant'}
|
{'Code': '06020000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'AGS', 'LongName': 'Div Atmospheric & Geospace Sciences'}}
|
{'SignBlockName': 'Roman Makarevich', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927207'}
|
High-latitude and polar regions present a unique set of challenges for continuous observations because of their remoteness and extreme and harsh environments. This project seeks to develop the next generation of small, low-power, autonomous, multi-instrument adaptive, ground-based geospace observation arrays, named AUtonomous Remote Geospace Observation and Research Array (AURORA). It is designed to fill large gaps in the currently existing ground-based instrument arrays in the high-latitude and polar regions. <br/><br/>With advanced technologies in solar panels, batteries, bidirectional satellite communication, low-power sensors (fluxgate and searchcoil magnetometers, radio receivers, etc.), and high-performance single-board computers, AURORA will enable year-round observations with cost-effective, multiple instruments in these remote logistically challenging locations. This will significantly improve the ability to study (1) interhemispheric asymmetries from the viewpoint of geomagnetic and ionospheric variability, (2) the mesoscale of solar-wind - magnetosphere - ionosphere coupling in high-latitude and polar regions, as well as other space weather phenomena. Deep-field autonomous observatories have the potential to co-locate instruments across disciplines in polar science and facilitate international collaborations. This project will also contribute to training the future workforce. It will support two early-career researchers including a female early-career scientist. Graduate and undergraduate students will participate in the research, assisting with instrumentation design and testing.<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.
|
07/15/2024
|
07/15/2024
|
None
|
Grant
|
47.050
|
1
|
4900
|
4900
|
2432887
|
{'FirstName': 'Michelle', 'LastName': 'Salzano', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michelle Salzano', 'EmailAddress': '[email protected]', 'NSF_ID': '000922304', 'StartDate': '07/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'SPACE SCIENCE INSTITUTE', 'CityName': 'BOULDER', 'ZipCode': '803012575', 'PhoneNumber': '7209745888', 'StreetAddress': '4765 WALNUT ST STE B', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Colorado', 'StateCode': 'CO', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'CO02', 'ORG_UEI_NUM': 'KCBXMSFGQGY3', 'ORG_LGL_BUS_NAME': 'SPACE SCIENCE INSTITUTE', 'ORG_PRNT_UEI_NUM': 'KCBXMSFGQGY3'}
|
{'Name': 'SPACE SCIENCE INSTITUTE', 'CityName': 'BOULDER', 'StateCode': 'CO', 'ZipCode': '803012575', 'StreetAddress': '4765 WALNUT ST STE B', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Colorado', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'CO02'}
|
{'Code': '420200', 'Text': 'Upper Atmospheric Facilities'}
|
2024~20000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2432887.xml'}
|
I-Corps: Translation Potential of an Immunotherapeutic Oncolytic Virus
|
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': 'Molly Wasko', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924749'}
|
The broader impact/commercial potential of this I-Corps project is based on the development of an immunotherapeutic virus vector for cancer treatment. This modified virus targets cancer cells and activates the immune system, generating an adaptive immune response and potential synergy with Immune Checkpoint Inhibitors. Current solutions do not offer both direct cancer cell destruction and immune system enhancement. Ultimately, this approach has the potential to significantly change cancer therapy and benefit a wide range of cancer patients.<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. The solution is based on the development of an immunotherapy and gene delivery platform that addresses the major hurdles for the success of oncolytic vaccines and gene therapy for solid tumors. The solution was developed and tested using a new generation of therapeutic vectors, based on vaccinia virus, that is able to directly kill cancer cells, activate the immune system against tumor antigens, and deliver therapeutic transgenes at tumor sites via blood circulation. In addition, the vectors in this solution combine with standard of care or immune checkpoint inhibitors and may result in complete eradication of tumors and metastases.<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.
|
06/25/2024
|
06/25/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2432981
|
{'FirstName': 'Ian', 'LastName': 'Mohr', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ian J Mohr', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A03NF', 'StartDate': '06/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'New York University Medical Center', 'CityName': 'NEW YORK', 'ZipCode': '100166402', 'PhoneNumber': '2122638822', 'StreetAddress': '550 1ST AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NY12', 'ORG_UEI_NUM': 'M5SZJ6VHUHN8', 'ORG_LGL_BUS_NAME': 'NEW YORK UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'New York University Grossman School of Medicine', 'CityName': 'NEW YORK', 'StateCode': 'NY', 'ZipCode': '100166402', 'StreetAddress': '430 East 29th Street', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'NY12'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2432981.xml'}
|
SBIR Phase I: Selective Ion Separation and Recovery for Wastewater Treatment
|
NSF
|
09/01/2024
|
08/31/2025
| 275,000 | 275,000 |
{'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 impacts of this Small Business Innovation Research (SBIR) Phase I project are in water management and resource recovery. Conventional wastewater treatment methods lack solute selectivity, leading to costly and energy-intensive inefficiencies and thwarting efforts to mitigate emerging contaminants. Waste streams may also contain valuable resources that could generate revenue if recovered. Further, improved water reuse operations are needed to address the growing demand for clean water. The technology presented in this project transcends the existing paradigm by offering a method for the highly selective separation of target solutes from water sources, creating multiple, distinct ionic products and substantially dewatering the feed source. In result, this technology may be used to simultaneously remove unwanted contaminants, recover valuable byproducts, and produce clean water for non-potable reuse. Various industries would benefit from this technology, but the ultimate aim is to lower the financial and infrastructural barriers to advanced treatment and reuse for economically disadvantaged communities. By significantly reducing the energy and maintenance costs of wastewater treatment and disposal, and enabling further cost-recuperation through resource recovery, this innovation is poised to greatly enhance the viability of water reuse, ensuring that all communities have equitable access to clean water and healthy ecosystems.<br/><br/><br/>The core technical innovation of the proposed technology lies in its ability to selectively separate specific ions from heterogeneous waste or raw water sources; such selectivity does not exist in current water treatment practice. The technology functions through the strategic implementation of energy-efficient electrochemical processes. This approach surpasses existing treatment conventions by not only performing selective exclusion, but by simultaneously generating four distinct, highly concentrated product streams that are differentiated by ion charge and valence, as well as an additional clean water stream that emerges during product concentration. This NSF SBIR Phase I project will focus on three main tasks: optimizing technical design for maximum solute selectivity and concentration, evaluating separation performance with representative wastewaters from three key industries, and scaling up the system for future pilot testing. Experimentation will validate total concentration and dewatering capacities, but initial estimates suggest products may be concentrated up to 10x their starting values and feed volume may be reduced by up to 88%. Evaluation with different waste effluents will determine the technology’s adaptability and marketability in different contexts. The successful completion of Phase I testing will lay the foundation for further commercial development of this innovative concept.<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.
|
08/22/2024
|
08/22/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2432982
|
{'FirstName': 'Aaron', 'LastName': 'Forbis-Stokes', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Aaron Forbis-Stokes', 'EmailAddress': '[email protected]', 'NSF_ID': '000808536', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'TRIANGLE ENVIRONMENTAL HEALTH INITIATIVE LLC', 'CityName': 'DURHAM', 'ZipCode': '277013794', 'PhoneNumber': '3364140252', 'StreetAddress': '105 HOOD ST STE 3', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'NC04', 'ORG_UEI_NUM': 'X6EJJK2HHMF1', 'ORG_LGL_BUS_NAME': 'TRIANGLE ENVIRONMENTAL HEALTH INITIATIVE LLC', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'TRIANGLE ENVIRONMENTAL HEALTH INITIATIVE LLC', 'CityName': 'DURHAM', 'StateCode': 'NC', 'ZipCode': '277013794', 'StreetAddress': '105 HOOD ST STE 3', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'NC04'}
|
{'Code': '537100', 'Text': 'SBIR Phase I'}
|
2024~275000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2432982.xml'}
|
C2H2 EAGER: Bridging Seasonal Physical Climate/Weather Prediction with Disease Forecasts
|
NSF
|
07/15/2024
|
06/30/2026
| 299,999 | 299,999 |
{'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'}
|
Environmental factors like temperature and precipitation affect mosquito abundance and range. These factors can ultimately affect the transmission and outbreak of vector-borne diseases like West Nile Virus. This disease is responsible for the most mosquito borne illnesses and associated deaths in the continental US. Despite the strong link between virus-carrying mosquito populations and meteorological conditions, West Nile Virus forecasts do not yet incorporate a number critical environmental factors. This research uses observed temperature and rainfall data, along with that predicted by models that calculate weather conditions months into the future, to improve West Nile Virus outbreak forecasts. The work will improve understanding of how this serious mosquito-borne illness will be impacted by climate change and the associated changing rainfall patterns and temperatures. Value of this work is that it links weather and climate forecast models that have inherent complexities and uncertainties to improve West Nile Virus-conducive conditions, providing improved understanding of relationships between weather and disease forecasts which will advance the national health. Other broader impacts include engagement and interaction with public health officials who will help identify critical study factors that will allow them to make more informed decisions about mitigation (e.g., mosquito spraying or other techniques) to prevent or curtail outbreaks of the disease. Development of effective public outreach/warnings/communication will be undertaken to raise public awareness of the conditions and incidences of mosquito infestations that can result in West Nile Virus so communities and individuals can take precautionary measures when conditions indicate a high risk for contracting the Virus. An additional impact is that this work builds relationships between geoscientists who understand the environment and Earth as a system and medical/health professionals who are focused on human health to accelerate advances in the prevention and protection of people exposed to conditions conducive to West Nile Virus.<br/><br/>This research builds upon preliminary results that will be extended to (1) strengthen the understanding of how climatic factors impact the transmission of West Nile Virus infections at the regional level; (2) include historical climate data and weather/climate forecasts into models to bolster disease prediction capabilities; (3) establish West Nile Virus disease forecasting model limits; and (4) determine the potential impact of future climate states on West Nile Virus transmission. Model development will use an array of legacy meteorological datasets in multivariate regressions to strengthen understanding of how regional climatic factors impact mosquito population dynamics conducive to disease transmission. Bayesian techniques will be used to develop multivariate disease forecast models that are informed by the climate-West Nile Virus relationships. Climate data from past years will allow quantification of the upper limit of forecast veracity and capability. Sensitivity analysis will be incorporated into operational weather/climate Earth system models from the short-term (i.e., daily to weekly) to long-term (i.e., sub-seasonal-to-seasonal) timescales. Revised climate models will be tested to determine their utility in modeling West Nile Virus outbreaks and infection rates. To this end, ensemble capabilities of numerical weather prediction models will be used to provide a “best” forecast, as compiled from the ensemble mean. Results will be used to identify potential ranges of outbreaks and to determine forecast uncertainties. Results of the research will be used to examine if West Nile Virus forecasts that include climate inputs outperform present baseline transmission predictions that do not include this information. The research will also examine tradeoffs between increased forecast lead-time and disease forecast accuracy and will look at the impact of future climate states on the geographic range of West Nile Virus as a result of increasing temperature regimes driven by 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.
|
07/11/2024
|
07/11/2024
|
None
|
Grant
|
47.050
|
1
|
4900
|
4900
|
2432999
|
[{'FirstName': 'Benjamin', 'LastName': 'Green', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Benjamin W Green', 'EmailAddress': '[email protected]', 'NSF_ID': '000689460', 'StartDate': '07/11/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Stanley', 'LastName': 'Benjamin', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Stanley Benjamin', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A07ML', 'StartDate': '07/11/2024', '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': 'NOAA /Global Systems Laboratory-David Skaggs Research Center', 'CityName': 'Boulder', 'StateCode': 'CO', 'ZipCode': '803090001', 'StreetAddress': '325 Broadway', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Colorado', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'CO02'}
|
{'Code': '300Y00', 'Text': 'Climate Impact on Human Health'}
|
2024~299999
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2432999.xml'}
|
Travel: Student Travel Support for 2025 IEEE Radio & Wireless Week (RWW)
|
NSF
|
08/01/2024
|
01/31/2025
| 25,000 | 25,000 |
{'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'}
|
The IEEE Radio & Wireless Week (RWW) covers a broad range of emerging research topics in radio wireless technologies, from theory to practical implementation, from integrated chips to large-scale systems, from kilohertz (kHz) to terahertz (THz), and from communications to sensing and space applications. It is sponsored by the IEEE Microwave Theory and Technology Society, with technical co-sponsorships from the IEEE Antennas and Propagation Society, the IEEE Aerospace and Electronic Systems Society, and the IEEE Geoscience and Remote Sensing Society. The 20th annual IEEE RWW will be held in San Juan, Puerto Rico on January 19-22, 2025. To support the training of the next-generation scientists and engineers working on 6G Wireless, this NSF grant will provide travel support for 25 students to present their research papers at the conference and learn the cutting-edge research and development of wireless technologies, systems, and applications. The travel grants will be awarded competitively to graduate students from U.S. universities who will present their accepted papers at the conference. The awardees will be selected by a committee of the conference and the paper quality will be considered in the selection process. The proposed travel support will have long-term and broad impacts on the participating students' career developments and contribute to the U.S. STEM workforce development.<br/><br/>The IEEE RWW in 2025 consists of five co-located sub-conferences: Topical Conference on Power Amplifiers for Wireless and Radio Applications (PAWR), Topical Meeting on Silicon Monolithic Integrated Circuits in RF Systems (SiRF), Topical Conference on Wireless Sensors and Sensor Networks (WiSNet), Space Hardware and Radio Conference (SHaRC), and Radio and Wireless Symposium (RWS). Students attending the conference will learn about the latest state-of-the-art wireless technologies in these topical areas covering devices, integrated circuits, antennas, system architectures, and emerging applications such as 6G Wireless and space communications/sensing.<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.
|
07/15/2024
|
07/15/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2433006
|
{'FirstName': 'Davi', 'LastName': 'V Q Rodrigues', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Davi V Q Rodrigues', 'EmailAddress': '[email protected]', 'NSF_ID': '000996801', 'StartDate': '07/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Texas at El Paso', 'CityName': 'EL PASO', 'ZipCode': '799688900', 'PhoneNumber': '9157475680', 'StreetAddress': '500 W UNIVERSITY AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '16', 'CONGRESS_DISTRICT_ORG': 'TX16', 'ORG_UEI_NUM': 'C1DEGMMKC7W7', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY OF TEXAS AT EL PASO', 'ORG_PRNT_UEI_NUM': 'C1DEGMMKC7W7'}
|
{'Name': 'University of Texas at El Paso', 'CityName': 'EL PASO', 'StateCode': 'TX', 'ZipCode': '799688900', 'StreetAddress': '500 W UNIVERSITY AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '16', 'CONGRESS_DISTRICT_PERF': 'TX16'}
|
{'Code': '756400', 'Text': 'CCSS-Comms Circuits & Sens Sys'}
|
2024~25000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433006.xml'}
|
FW-HTF-RL/Collaborative Research: Future of Digital Facility Management (Future of DFM)
|
NSF
|
12/01/2023
|
12/31/2027
| 775,438 | 775,438 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Daniel McAdams', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924654'}
|
This Future of Work at the Human-Technology Frontier - Research: Large (FW-HTF-RL) award supports research to address the critical shift towards digital transformation in the facility management industry, a sector grappling with technological and workforce changes. The industry is on the verge of adopting advanced Information and Communication Technology, Internet of Things, and Big Data paradigms, aiming to make traditional operations more data-driven to meet organizational and national energy reduction goals. These advances target multiple improvements, including occupant comfort and health, system resilience, energy performance, and operational cost reductions. The transition necessitates facility managers to adapt to increased data volumes and new forms of human-machine interaction, thereby necessitating upskilling and reskilling. The project also recognizes the skills shortage in the industry, highlighting the need for efforts from industry leaders, educators, and policymakers to prepare a workforce for the future of facility management.<br/><br/>The technical goals of this project aim at addressing the digital transformation challenges within facility management. The first objective is to construct a digital twin ecosystem for a facility, enhancing the role of facility managers by providing them with physical and cognitive assistance. The second objective involves developing a multi-modal user interface to promote effective interaction within the digital ecosystem, allowing communication between occupants, FMs, and other stakeholders. Thirdly, the project will gauge facility managers' readiness to utilize the digital twin technology, intending to refine the technology continuously and identify any barriers to adoption. The final objective is to study the impacts of adopting this technology on facility managers, occupants, and facility owners, incorporating different perspectives to develop comprehensive solutions to the industry's challenges. Additionally, project work with industry leaders and facility managers will identify the necessary training and educational initiatives that can equip the current and future workforce with the skills required to keep pace with digital transformation. Such initiatives will involve curating curricula that are aligned with technological advancements, enhancing existing training programs, and designing new ones to fill the skills gap. Collaboration activities will also seek to inspire and attract diverse talents to the industry, thus fostering a work environment that is ready for the future of digital facility management.<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.
|
07/01/2024
|
07/01/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2433037
|
{'FirstName': 'Somayeh', 'LastName': 'Asadi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Somayeh Asadi', 'EmailAddress': '[email protected]', 'NSF_ID': '000627468', 'StartDate': '07/01/2024', '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': '103Y00', 'Text': 'FW-HTF Futr Wrk Hum-Tech Frntr'}
|
2023~775438
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433037.xml'}
|
I-Corps: Translation Potential of Back Support Exoskeleton Technology
|
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': 'Ruth Shuman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922160'}
|
The broader impact of this I-Corps project is the development of a back support device that assists users with bending and lifting tasks. Currently, more than 25% of the 80 million U.S. workers must lift objects that weigh more than 50 pounds on a regular basis. As a result, more than 120,000 of these workers sustain lower back injuries each year from repetitive lifting resulting in productivity losses, high employee turnover, and lower quality of life. This technology is a back exoskeleton or exosuit, which relieves loads from the back and reduces the risk of injuries or pain. This technology may be used in occupations such as manufacturing, logistics, nursing and emergency medicine, construction, mining, and retail stores. Each of these occupations has a relatively high rate of back injuries due to the repetitive lifting or lifting of heavy objects required for the job. <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 a back support exoskeleton that assists users with bending and lifting tasks. The technology is designed to make a lifted object feel between 35-50 pounds lighter to the user's back. The design is completely passive, using no motors or batteries. Instead, it utilizes a lightweight fiberglass leaf spring that stores energy when bending and releases the energy to assist when standing up. The exoskeleton looks and feels like a lightweight backpack with leg straps, weighing only 5.5 pounds, and it can be put on in 15 seconds. The combination of the fiberglass spring and a specifically designed differential mechanism allow users to seamlessly go about their work while the device assists them with lifting tasks, without hindering them during walking and without needing to engage or disengage the exoskeleton. A prototype has been shown to decrease muscle activity by over 30% during lifting, which reduces strain on the back, lowering the risk of injury. In addition, the technology also decreases the energy required during lifting, improving overall user well-being. Compared to other back exoskeletons, this device is simpler yet provides three times more support to the back, which may help to reduce back injuries.<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
|
2433053
|
{'FirstName': 'Alan', 'LastName': 'Asbeck', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Alan Asbeck', 'EmailAddress': '[email protected]', 'NSF_ID': '000707410', 'StartDate': '06/17/2024', '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': '240616100', 'StreetAddress': '300 TURNER ST NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'VA09'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433053.xml'}
|
SBIR Phase I: ReleaseChecker: Lastline Software Supply Chain Security via GPU-accelerated Binary Diffing
|
NSF
|
09/01/2024
|
08/31/2025
| 273,383 | 273,383 |
{'Value': 'Standard Grant'}
|
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
|
{'SignBlockName': 'Peter Atherton', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928772'}
|
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to introduce unique AI-powered code diffing capabilities to defend against software supply chain attacks, capabilities that are not yet available in other software supply chain security solutions. This innovation offers several benefits. Firstly, by reducing cybersecurity operation costs, it improves the competitiveness of U.S. companies, allowing them to allocate resources more efficiently. Secondly, it bolsters software supply chain security, significantly reducing the risk of cyberattacks and protecting sensitive data for governments, enterprises, critical infrastructures, and individuals. Additionally, this innovation will extend our understanding of how to apply AI to program analysis for cybersecurity, including binary code disassembling, function feature extraction and embedding, model training, and optimization. It establishes a new program analysis pipeline based on the latest AI technology, which can be extended to many other cybersecurity applications.<br/><br/>This Small Business Innovation Research (SBIR) Phase I project addresses the critical need for enhancing software supply chain security and compliance. Unlike other solutions that monitor each stage of the software supply chain, this project aims to leverage AI-powered code diffing technology to precisely and efficiently find the differences between two released versions of the same software. It further combines software composition analysis and large language models (LLMs) to understand the risks associated with these differences. This solution acts as the final check before the software is released or deployed. The anticipated results include improved accuracy and efficiency in diffing analysis and comprehension, as well as a prototype for testing and commercialization.<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.
|
08/20/2024
|
08/20/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2433062
|
{'FirstName': 'Xunchao', 'LastName': 'Hu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xunchao Hu', 'EmailAddress': '[email protected]', 'NSF_ID': '000750332', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'DEEPBITS TECHNOLOGY LLC', 'CityName': 'RIVERSIDE', 'ZipCode': '925082974', 'PhoneNumber': '9518276437', 'StreetAddress': '20871 WESTBURY RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '39', 'CONGRESS_DISTRICT_ORG': 'CA39', 'ORG_UEI_NUM': 'JAKLV5H8KAQ3', 'ORG_LGL_BUS_NAME': 'DEEPBITS TECHNOLOGY INC.', 'ORG_PRNT_UEI_NUM': 'JAKLV5H8KAQ3'}
|
{'Name': 'DEEPBITS TECHNOLOGY Inc.', 'CityName': 'RIVERSIDE', 'StateCode': 'CA', 'ZipCode': '925082974', 'StreetAddress': '20871 WESTBURY RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '39', 'CONGRESS_DISTRICT_PERF': 'CA39'}
|
{'Code': '537100', 'Text': 'SBIR Phase I'}
|
2024~273383
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433062.xml'}
|
SBIR Phase I: High Light-Throughput Electrodes for Top-Emitting and Transparent OLED Displays
|
NSF
|
01/01/2025
|
12/31/2025
| 274,953 | 274,953 |
{'Value': 'Standard Grant'}
|
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
|
{'SignBlockName': 'Ela Mirowski', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922936'}
|
The broader/commercial impact of this Small Business Innovation Research Phase I project is the generation of more efficient and brighter organic light emitting diodes (OLEDs) which are the individual lighting emitting elements within the displays of our cell phones, tablets, and smart watches. This project seeks to provide the same quality of OLED display but at 1.5 higher efficiency, thereby allowing a phone, for example, to run at 11% less power, with potential savings as high as 19%. If one considers the power used by the 4.9 billion cell phones worldwide (equivalent to the power generation for the state of Delaware) the cumulative saved power provides a significant effect in aggregate. Beyond large aggregate energy savings, this project provides other benefits to the end consumer. These include better brightness for outdoor usage of phones/watches/tablets, better viewing in augmented reality or virtual reality headsets, and even potential improvements in see-through display applications.<br/><br/>The efficient and brighter OLEDs are enabled by the project’s ultra-thin chemical adlayer which is placed on top of the materials in the OLED stack, resulting in superior transparency of the top-laying metal electrode. This circumvents the problem that has long vexed OLED display manufacturers, specifically, that the thin metal electrode providing electrical current to the materials in the OLED stack needs to be both transparent and conductive. Normally, reducing the thickness of the electrode improves transparency, but severely diminishes conductivity. As such, this thin metal cannot be reduced any further, and still limits the amount of light that can pass from the OLED. The project avoids this issue by making the metal a more uniform (continuous) layer by reducing self-aggregation of the metal, allowing the metal to retain high conductivity at a much lower thickness. This effect is enabled by the project’s technology, which is an unusually effective nucleation inducer. The project validates the effectiveness of the chemical adlayer in OLED pixels and then optimizes chemical structure for increased effectiveness. The resultant chemical treatment is then capable of reaching the targeted metric of 1.5 more efficient/brightness OLED pixel.<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
|
47.084
|
1
|
4900
|
4900
|
2433105
|
{'FirstName': 'Jacob', 'LastName': 'Ciszek', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jacob W Ciszek', 'EmailAddress': '[email protected]', 'NSF_ID': '000537815', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'MOLECULAR INTERFACES, LLC', 'CityName': 'CHICAGO', 'ZipCode': '606063607', 'PhoneNumber': '7735083107', 'StreetAddress': '200 W MADISON ST STE 3300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'IL07', 'ORG_UEI_NUM': 'M1JQY56LJY57', 'ORG_LGL_BUS_NAME': 'MOLECULAR INTERFACES, LLC', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'MOLECULAR INTERFACES, LLC', 'CityName': 'CHICAGO', 'StateCode': 'IL', 'ZipCode': '606601537', 'StreetAddress': '1068 W. Sheridan Rd', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'IL09'}
|
{'Code': '537100', 'Text': 'SBIR Phase I'}
|
2024~274953
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433105.xml'}
|
SBIR Phase I: A low-cost field-use DNA-based rapid diagnostic device for plant diseases
|
NSF
|
11/15/2024
|
07/31/2025
| 270,128 | 270,128 |
{'Value': 'Standard Grant'}
|
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
|
{'SignBlockName': 'Ela Mirowski', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922936'}
|
The broader/commercial impact of this Small Business Innovation Research Phase I project is to enable farmers to take early action against destructive plant diseases to protect their crops, reducing reliance on harmful pesticides. Climate change and global trade have led to an increased spread of harmful pests and plant diseases like Citrus Greening. These diseases threaten the world's food supply and cost farmers billions of dollars each year. Farmers are forced to rely heavily on pesticides, harming the environment, human health, and ultimately, their sustainability. Currently, identifying these diseases often involves sending samples to centralized labs, which can be slow, inconvenient, and inefficient. This Phase I project aims to develop a user-friendly, affordable testing device that allows farmers to quickly identify plant diseases right in their fields. This early identification of plant diseases would enable the farmers to practice more sustainable farming methods that would lead to higher crop yields, improved food security, maintain U.S. competitiveness in the global food trade and preserve jobs in the agricultural industry. This on-site testing and data-driven decision making by less-skilled farm workers also leads to increased science education, thus serving NSF’s mission.<br/><br/>On-site testing by farm technicians is a critical need for the early detection of destructive plant diseases like Citrus Greening in the pre-symptomatic phase to reduce the spread of infection and to lessen the prophylactic use of pesticides. This project aims to enable such rapid on-site testing of vector-borne plant diseases through development of a low-cost, battery-operated, accurate, nucleic acid-based molecular diagnostic test kit that can process diverse, hard-to-lyse plant tissue samples and produces easily-readable results in 30 minutes. The main goals of this Phase I project are to develop a simple, field use-friendly hardware kit for sample homogenization, nucleic acid extraction, isothermal amplification and signal readout and to formulate optimal formulations for lysis, extraction and amplification reagents. The outcome of this 9-month project will be a universal hardware kit and a Huanglongbing (HLB) disease-specific reagent kit that would be designed and optimized to have >90% sensitivity and 100% specificity for Candidatus liberibacter asiaticus (CLas), the causative pathogen of HLB disease. The universal hardware kit can be used with other pathogen-specific reagent kits that would be developed in the future.<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.
|
08/20/2024
|
08/20/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2433122
|
{'FirstName': 'Prasanna', 'LastName': 'Thwar Krishnan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Prasanna Thwar Krishnan', 'EmailAddress': '[email protected]', 'NSF_ID': '000996897', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'EVOLVE GENOMIX, INC.', 'CityName': 'PLEASANTON', 'ZipCode': '945668446', 'PhoneNumber': '6505500908', 'StreetAddress': '1249 QUARRY LN STE 130', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '14', 'CONGRESS_DISTRICT_ORG': 'CA14', 'ORG_UEI_NUM': 'S9BWNM83K9D1', 'ORG_LGL_BUS_NAME': 'EVOLVE GENOMIX, INC.', 'ORG_PRNT_UEI_NUM': 'S9BWNM83K9D1'}
|
{'Name': 'EVOLVE GENOMIX, INC.', 'CityName': 'PLEASANTON', 'StateCode': 'CA', 'ZipCode': '945668446', 'StreetAddress': '1249 QUARRY LN STE 130', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '14', 'CONGRESS_DISTRICT_PERF': 'CA14'}
|
{'Code': '537100', 'Text': 'SBIR Phase I'}
|
2024~270128
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433122.xml'}
|
SBIR Phase I: AI-Powered Low-dose, Low-cost, High-Quality CT imaging
|
NSF
|
09/01/2024
|
08/31/2025
| 275,000 | 275,000 |
{'Value': 'Standard Grant'}
|
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
|
{'SignBlockName': 'Henry Ahn', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927069'}
|
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project stem from the development of methods to display and diagnose heart rhythms more accurately and continuously after cardiac surgery. Inadequate post-operative rhythm monitoring remains a significant concern in over 400,000 cardiac surgeries in the United States (US), 30-50% of which result in arrhythmias. Arrhythmias, especially when missed or diagnosed late due to inaccurate or delayed monitoring, often lead to worse patient outcomes, including stroke, cardiac dysfunction, heart failure, and death. These issues are associated with hospital expenses exceeding $9,000 per hospital stay per patient within the growing $8-billion US post-operative cardiac care market. Beyond the significant economic impact, more accurate and continuous post-operative cardiac rhythm monitoring would provide substantial, potentially lifesaving benefits to human health.<br/><br/>This Small Business Technology Transfer (STTR) Phase I project aims to address the limitations of current post-operative rhythm diagnosis using standard surface-based electrocardiogram (ECG) monitoring. The inadequacy of atrial signal quality makes it challenging or impossible for providers to interpret rhythm accurately. Additionally, significant variations in patient and ECG characteristics limit the utility of current rhythm monitoring systems, impacting the optimal care of critically ill patients. This project will develop and validate a method for continuous rhythm diagnosis and display using the highest quality atrial electrogram. The diagnosis method will be developed, validated, and optimized with real patient data, ensuring adaptability to varying patient, rhythm, and ECG characteristics. The anticipated outcome is a shift from the current labor-intensive, non-real-time, and inconveniently displayed methodology, which requires specialized training, to a real-time, more accurate, continuous, and easily accessible diagnosis system. If successful, this project is expected to substantially improve post-operative care and establish a more accurate standard for post-operative rhythm assessment.<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.
|
08/22/2024
|
08/22/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2433137
|
{'FirstName': 'Linxi', 'LastName': 'Shi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Linxi Shi', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A067Y', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'NEURALTRAK, INC', 'CityName': 'LOS ALTOS', 'ZipCode': '940223911', 'PhoneNumber': '5083695989', 'StreetAddress': '511 LASSEN ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '16', 'CONGRESS_DISTRICT_ORG': 'CA16', 'ORG_UEI_NUM': 'XHJSFKKWBDU5', 'ORG_LGL_BUS_NAME': 'NEURALTRAK, INC', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'NEURALTRAK, INC', 'CityName': 'LOS ALTOS', 'StateCode': 'CA', 'ZipCode': '940223911', 'StreetAddress': '511 LASSEN ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '16', 'CONGRESS_DISTRICT_PERF': 'CA16'}
|
{'Code': '537100', 'Text': 'SBIR Phase I'}
|
2024~275000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433137.xml'}
|
I-Corps: Translation potential of virtual reality simulation technology to enhance empathetic concern and compassionate care among medical students and healthcare professionals
|
NSF
|
09/01/2024
|
02/28/2025
| 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': 'Ruth Shuman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922160'}
|
The broader impact of this I-Corps project is the development of a healthcare education platform to foster empathy, cultural competence, and essential skills for patient-centered care. Currently, there is a need for educational resources for healthcare systems and education programs aiming to meet new competencies required by the American Association of Colleges of Nursing and other healthcare accreditation agencies. This technology simulates patient scenarios and delivers micro-learning interventions providing an immersive experience, placing learners in the patient’s perspective. The approach may be integrated into existing curricula, addressing the critical need for empathy and cultural competence in patient care training, particularly in low-income and culturally diverse communities. In addition, this technology has the potential to transform healthcare training and patient care standards, offering a scalable solution for healthcare systems and education programs.<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 a healthcare education platform that utilizes advanced 180º virtual reality simulation technology to deliver immersive, micro-story patient interventions. The goal is to enhance empathetic concern and compassionate care among healthcare learners and professionals. These microlearning interventions are grounded in evidence-based research and validated through neurophysiological, behavioral, attitudinal, and self-report testing. Each intervention is designed to simulate patients’ perspectives, providing a rapid, impactful experience in less than five minutes. These interventions are complemented by validated reflective protocols that can be facilitated virtually, in person, or asynchronously through interactive video or artificial intelligence tools. This combination enhances empathy and facilitates the development of the critical awareness of systemic barriers to compassionate care. In addition, this micro-learning strategy seamlessly integrates into existing curricula, meeting new accreditation standards and addressing the critical need for empathy and cultural competence in patient care training. This solution is particularly important for low-income and culturally diverse communities. The 180º video capture technology provides an immersive experience that can be developed for a wide range of scenarios, effectively transporting the learner into the perspective of future patients.<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
|
2433154
|
{'FirstName': 'Maria', 'LastName': 'Keckler', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Maria H Keckler', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A09J5', 'StartDate': '07/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'San Diego State University Foundation', 'CityName': 'SAN DIEGO', 'ZipCode': '921821901', 'PhoneNumber': '6195945731', 'StreetAddress': '5250 CAMPANILE DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '51', 'CONGRESS_DISTRICT_ORG': 'CA51', 'ORG_UEI_NUM': 'H59JKGFZKHL7', 'ORG_LGL_BUS_NAME': 'SAN DIEGO STATE UNIVERSITY FOUNDATION', 'ORG_PRNT_UEI_NUM': 'H59JKGFZKHL7'}
|
{'Name': 'San Diego State University Foundation', 'CityName': 'SAN DIEGO', 'StateCode': 'CA', 'ZipCode': '921821901', 'StreetAddress': '5250 CAMPANILE DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '51', 'CONGRESS_DISTRICT_PERF': 'CA51'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433154.xml'}
|
Doctoral Dissertation Research: The Role of Material Culture in Community Designation
|
NSF
|
08/01/2024
|
07/31/2025
| 29,149 | 29,149 |
{'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 research investigates how multicultural communities negotiate their identities following migration. Over the last thirty years, archaeologists have expanded the study of migration from a topic limited to identifying the movement of people, to one that explores the different forms of interaction between local and migrant populations over time. Archaeology is well-placed to assess change over time in the interactions of local and migrant populations at various group sizes. By studying material culture, archaeology can address the extent to which migrants remained distinct versus becoming integrated into the newly formed multicultural communities. This is of particular concern now, as national and transnational migration is a current topic of discourse worldwide. Although migration is often framed as a "problem" to be solved, the investigators emphasize that migration is not a problem but something that humans have always done and always needed to navigate. In particular, this work contributes to how people navigate identity in multicultural communities. Additionally, this work funds an undergraduate research assistant, helping them understand and experience the research process by doing archival and museum collections work.<br/><br/>The project examines how corrugated ceramics, or hand-built vessels with exposed coils, were used as a form of identity negotiation after a large migration of late prehistoric people. These ceramics are examined to address the question of whether migrants and hosts remained distinct groups or alternatively formed more cohesive communities. The researchers use these vessels to identify communities of potters at past settlements by looking at the technological and stylistic characteristics of each vessel. When examined together, subtle characteristics of a vessel create a "signature" for a potter or potting community because people learned to make these vessels differently. The investigator looks at vessels and archives from six archaeological sites before and after the migration. These sites were excavated from the 1940s to 1990s. The data set created by this analysis examines how pots were made at different sites and even within the same site before and after the migrations. These analyses reveal connections between the ways people were taught to make vessels across the region and identify communities that make corrugated vessels similarly, informing the researchers about how potters who migrated into new areas integrated (or not) into their new community. The team will thus contribute knowledge regarding how social dynamics were navigated for comparison to other case studies around the globe.<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
|
2433175
|
[{'FirstName': 'Barbara', 'LastName': 'Mills', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Barbara J Mills', 'EmailAddress': '[email protected]', 'NSF_ID': '000130875', 'StartDate': '07/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Rebecca', 'LastName': 'Harkness', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rebecca J Harkness', 'EmailAddress': '[email protected]', 'NSF_ID': '000927813', 'StartDate': '07/26/2024', 'EndDate': None, 'RoleCode': 'Co-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': '857210030', 'StreetAddress': 'Southwest Archaeology Lab, Haury Building Room 402', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Arizona', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'AZ07'}
|
{'Code': '760600', 'Text': 'Archaeology DDRI'}
|
2024~29149
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433175.xml'}
|
EAGER: PBI: Modeling Place-based Innovation by Leveraging AI-Enabled Dynamic Graph Techniques
|
NSF
|
09/01/2024
|
08/31/2026
| 295,591 | 295,591 |
{'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 (PBI) plays a crucial role in driving regional economic development and addressing community needs by leveraging existing research institutions, universities, and industries. However, critical gaps remain in our understanding of the duration and investments required to bring products from initial research and development through translation phases to market availability. Similarly, the impact of workforce development approaches on participant career trajectories and earnings potential remains unclear. This project aims to provide novel modeling solutions to quantify and predict PBI-related quantities, considering the complex interplay of geography, technology domain, and cross-sector partnerships. The outcomes of this research may benefit various stakeholders, including companies, nonprofits, governments, universities, and individuals, by providing crucial insights into the timelines, investments, and contextual dependencies associated with converting ideas into societal impacts.<br/><br/>The proposed study will develop a deep graph neural network-based foundation model to quantify and predict PBI-related quantities, addressing the challenges posed by data scarcity and the multi-faceted complexity of diverse geography and technology domains. The model will be pre-trained using widely accessible public datasets and fine-tuned on place- or domain-specific datasets, enabling effective handling of data scarcity. The research design focuses on three main aspects of PBI: modeling the time and capital requirements for product development and commercialization; assessing the impacts of workforce development and diversity, equity, inclusion, and accessibility (DEIA) factors on career outcomes; and accounting for the influence of contextual factors such as geography, technology, and cross-sector partnerships. The methodology will leverage cutting-edge AI techniques, such as multi-view learning and graph Transformers, to provide an integrated model for PBI-related modeling and predictions. The project has high potential to significantly advance our understanding of PBI dynamics and complex interplays of factors influencing innovation, workforce development, and regional economic growth. The developed foundation model can serve as a powerful tool for decision-makers, enabling them to make informed choices regarding resource allocation, strategy development, and policy implementation. Moreover, the project's innovative approach will help open up new research avenues in the field of PBI, fostering further advancements in our understanding of innovation ecosystems and their societal impact.<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
|
2433190
|
[{'FirstName': 'Qiang', 'LastName': 'Ye', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Qiang Ye', 'EmailAddress': '[email protected]', 'NSF_ID': '000482987', 'StartDate': '07/09/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Qiang', 'LastName': 'Cheng', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Qiang S Cheng', 'EmailAddress': '[email protected]', 'NSF_ID': '000309382', 'StartDate': '07/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'University of Kentucky Research Foundation', 'CityName': 'LEXINGTON', 'ZipCode': '405260001', 'PhoneNumber': '8592579420', 'StreetAddress': '500 S LIMESTONE', 'StreetAddress2': '109 KINKEAD HALL', 'CountryName': 'United States', 'StateName': 'Kentucky', 'StateCode': 'KY', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'KY06', 'ORG_UEI_NUM': 'H1HYA8Z1NTM5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF KENTUCKY RESEARCH FOUNDATION, THE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Kentucky Research Foundation', 'CityName': 'LEXINGTON', 'StateCode': 'KY', 'ZipCode': '405260001', 'StreetAddress': '500 S LIMESTONE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Kentucky', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'KY06'}
|
{'Code': '301Y00', 'Text': 'NSF Engines - Type 2'}
|
2024~295591
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433190.xml'}
|
RAPID: Evolving risk dynamics between stakeholders during the H5N1 outbreak in dairy cattle
|
NSF
|
10/01/2024
|
09/30/2025
| 200,000 | 200,000 |
{'Value': 'Standard Grant'}
|
{'Code': '04050000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SES', 'LongName': 'Divn Of Social and Economic Sciences'}}
|
{'SignBlockName': "Robert O'Connor", 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927263'}
|
The 2024 outbreaks of H5N1 avian influenza in U.S. dairy cattle across multiple states represents a significant shift as this virus historically has affected mainly wild and domestic birds, not cows. These outbreaks are continuing to occur, posing risks to both human health and the stability of the dairy industry. Because the current scientific understanding of how the virus transmits in this new host is not fully known, designing effective guidelines or rules to control the spread of H5N1 is difficult. Such scientific understanding is critical for developing federal and state decisions, but also in guiding the actions by non-governmental stakeholders to mitigate risk. These decisions and actions are shaped by H5N1 information, risk perceptions, and understanding of the causes of the problem. This project enhances national health interests by investigating how different stakeholders, from government officials to the general public, use and perceive information about H5N1. The insights gained from this research help guide better communication and decision making for safeguarding public and animal health. <br/><br/>This proposal seeks to understand what information informs decisions at the federal and state levels and compare this to the information guiding veterinarians and the U.S. public in their risk perceptions and decision making. This project integrates interviews of federal and state human and animal health officials, panel surveys of accredited veterinarians, and the general public, to capture changes within and among stakeholder groups in information use, risk perceptions, and decisions over time. The research provides a unique opportunity to systematically assess how well-aligned these risk dimensions are across different stakeholder levels, providing a comprehensive perspective of how evolving and competing concerns influence the management of this crisis.<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.
|
06/25/2024
|
06/25/2024
|
None
|
Grant
|
47.075
|
1
|
4900
|
4900
|
2433191
|
[{'FirstName': 'Elizabeth', 'LastName': 'Shanahan', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Elizabeth A Shanahan', 'EmailAddress': '[email protected]', 'NSF_ID': '000086525', 'StartDate': '06/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Rob', 'LastName': 'DeLeo', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rob A DeLeo', 'EmailAddress': '[email protected]', 'NSF_ID': '000757992', 'StartDate': '06/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Manuel', 'LastName': 'Ruiz Aravena', 'PI_MID_INIT': 'I', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Manuel I Ruiz Aravena', 'EmailAddress': '[email protected]', 'NSF_ID': '000963770', 'StartDate': '06/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Montana State University', 'CityName': 'BOZEMAN', 'ZipCode': '59717', 'PhoneNumber': '4069942381', 'StreetAddress': '216 MONTANA HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Montana', 'StateCode': 'MT', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'MT01', 'ORG_UEI_NUM': 'EJ3UF7TK8RT5', 'ORG_LGL_BUS_NAME': 'MONTANA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Montana State University', 'CityName': 'BOZEMAN', 'StateCode': 'MT', 'ZipCode': '59717', 'StreetAddress': '216 MONTANA HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Montana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'MT01'}
|
{'Code': '132100', 'Text': 'Decision, Risk & Mgmt Sci'}
|
2024~200000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433191.xml'}
|
Collaborative Research: EPIIC: Cross-Continental Collaboration Coalition (C4)
|
NSF
|
09/01/2024
|
08/31/2027
| 370,000 | 370,000 |
{'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'}
|
The Cross-Continental Collaboration Coalition (C4) project is an interdisciplinary endeavor among five primarily undergraduate, four-year institutions—California State University, Chico; University of Central Oklahoma; Central Washington University; State University of New York (SUNY) Oswego; and Weber State University—to address the multifaceted challenges encountered in higher education today. One of the central challenges the investigators aim to tackle is the imperative to strengthen industry partnerships. Recognizing the pivotal role of industry collaboration in driving innovation and enhancing educational outcomes, each institution within the C4 cohort is committed to establishing and expanding regional innovation partnerships. These partnerships will serve as conduits for knowledge exchange, collaborative research projects, industry-informed curriculum realignment and experiential learning opportunities for students. By forging strong ties with industry stakeholders, the project seeks to ensure that educational programs at the C4 institutions remain relevant and responsive to the evolving needs of the workforce. Offering innovative programs tailored to meet the needs of employers, enhances the employability and career readiness of the C4 graduates. Another critical area of focus for the C4 project is the enhancement of research capacity. Robust research capabilities are essential for advancing knowledge, driving economic growth, and addressing pressing societal challenges. To this end, the C4 institutions are investing in research infrastructure, faculty development initiatives, and interdisciplinary collaboration platforms. By fostering a culture of innovation and inquiry, the investigators aim to position the C4 institutions as leaders in cutting-edge research and technology development. In addition to these institutional-level initiatives, the C4 project emphasizes cohort-wide collaboration and knowledge sharing. Through regular meetings, workshops, and joint initiatives, members of the C4 cohort exchange best practices, co-create innovative solutions, and support one another in achieving shared goals.<br/><br/>The C4 project emphasizes cohort-wide collaboration and knowledge sharing. Through regular meetings, workshops, and joint initiatives, members of the C4 cohort exchange best practices, co-create innovative solutions, and support one another in achieving shared goals. This project will contribute to the advancement of "best practices" in key areas of higher education and industry collaboration. Through collaborative efforts, participating institutions will identify and implement effective strategies for building vibrant regional innovation ecosystems and fostering interdisciplinary research and education. By leveraging the collective expertise of faculty and industry partners, the project will generate new knowledge, technologies, and approaches that can be adopted and replicated by other institutions facing similar challenges. Moreover, by integrating experiential learning opportunities and industry partnerships into academic programs, the project will enrich student learning experiences and prepare them for successful careers in dynamic and competitive fields. The potential impacts of the proposed project extend across multiple dimensions, including institutional, regional, and societal levels. At the institutional level, the project will enhance the reputation and competitiveness of participating institutions by strengthening their ties with industry partners and expanding their research capabilities. Additionally, by aligning academic programs with workforce needs, the project will enhance student outcomes and promote social mobility. The investigators expect this collaboration to impact the lives of 11,425 students annually. Regionally, the project will catalyze economic development by fostering innovation and entrepreneurship, creating job opportunities, and driving technological advancements. Furthermore, by promoting collaboration and knowledge sharing among institutions, the project will contribute to the broader landscape of higher education, inspiring innovation and excellence in teaching, research, and community engagement. Overall, the project will leave a lasting positive impact on participating institutions, their communities, and the higher education sector as a whole.<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.
|
07/29/2024
|
07/29/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2433214
|
[{'FirstName': 'Sanjeewa', 'LastName': 'Gamagedara', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sanjeewa B Gamagedara', 'EmailAddress': '[email protected]', 'NSF_ID': '000986623', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Evan', 'LastName': 'Lemley', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Evan C Lemley', 'EmailAddress': '[email protected]', 'NSF_ID': '000357050', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'University of Central Oklahoma', 'CityName': 'EDMOND', 'ZipCode': '730345207', 'PhoneNumber': '4059742538', 'StreetAddress': '100 N UNIVERSITY DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oklahoma', 'StateCode': 'OK', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'OK05', 'ORG_UEI_NUM': 'TVYWG7KY4XL8', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CENTRAL OKLAHOMA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Central Oklahoma', 'CityName': 'EDMOND', 'StateCode': 'OK', 'ZipCode': '730345207', 'StreetAddress': '100 N UNIVERSITY DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oklahoma', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'OK05'}
|
{'Code': '285Y00', 'Text': 'EPIIC-Enbl Part Incr Innov Cap'}
|
2024~370000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433214.xml'}
|
Collaborative Research: EPIIC: Cross-Continental Collaboration Coalition (C4)
|
NSF
|
09/01/2024
|
08/31/2027
| 399,998 | 399,998 |
{'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'}
|
The Cross-Continental Collaboration Coalition (C4) project is an interdisciplinary endeavor among five primarily undergraduate, four-year institutions—California State University, Chico; University of Central Oklahoma; Central Washington University; State University of New York (SUNY) Oswego; and Weber State University—to address the multifaceted challenges encountered in higher education today. One of the central challenges the investigators aim to tackle is the imperative to strengthen industry partnerships. Recognizing the pivotal role of industry collaboration in driving innovation and enhancing educational outcomes, each institution within the C4 cohort is committed to establishing and expanding regional innovation partnerships. These partnerships will serve as conduits for knowledge exchange, collaborative research projects, industry-informed curriculum realignment and experiential learning opportunities for students. By forging strong ties with industry stakeholders, the project seeks to ensure that educational programs at the C4 institutions remain relevant and responsive to the evolving needs of the workforce. Offering innovative programs tailored to meet the needs of employers, enhances the employability and career readiness of the C4 graduates. Another critical area of focus for the C4 project is the enhancement of research capacity. Robust research capabilities are essential for advancing knowledge, driving economic growth, and addressing pressing societal challenges. To this end, the C4 institutions are investing in research infrastructure, faculty development initiatives, and interdisciplinary collaboration platforms. By fostering a culture of innovation and inquiry, the investigators aim to position the C4 institutions as leaders in cutting-edge research and technology development. In addition to these institutional-level initiatives, the C4 project emphasizes cohort-wide collaboration and knowledge sharing. Through regular meetings, workshops, and joint initiatives, members of the C4 cohort exchange best practices, co-create innovative solutions, and support one another in achieving shared goals.<br/><br/>The C4 project emphasizes cohort-wide collaboration and knowledge sharing. Through regular meetings, workshops, and joint initiatives, members of the C4 cohort exchange best practices, co-create innovative solutions, and support one another in achieving shared goals. This project will contribute to the advancement of "best practices" in key areas of higher education and industry collaboration. Through collaborative efforts, participating institutions will identify and implement effective strategies for building vibrant regional innovation ecosystems and fostering interdisciplinary research and education. By leveraging the collective expertise of faculty and industry partners, the project will generate new knowledge, technologies, and approaches that can be adopted and replicated by other institutions facing similar challenges. Moreover, by integrating experiential learning opportunities and industry partnerships into academic programs, the project will enrich student learning experiences and prepare them for successful careers in dynamic and competitive fields. The potential impacts of the proposed project extend across multiple dimensions, including institutional, regional, and societal levels. At the institutional level, the project will enhance the reputation and competitiveness of participating institutions by strengthening their ties with industry partners and expanding their research capabilities. Additionally, by aligning academic programs with workforce needs, the project will enhance student outcomes and promote social mobility. The investigators expect this collaboration to impact the lives of 11,425 students annually. Regionally, the project will catalyze economic development by fostering innovation and entrepreneurship, creating job opportunities, and driving technological advancements. Furthermore, by promoting collaboration and knowledge sharing among institutions, the project will contribute to the broader landscape of higher education, inspiring innovation and excellence in teaching, research, and community engagement. Overall, the project will leave a lasting positive impact on participating institutions, their communities, and the higher education sector as a whole.<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.
|
07/29/2024
|
07/29/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2433215
|
[{'FirstName': 'Charles', 'LastName': 'Pooler', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Charles J Pooler', 'EmailAddress': '[email protected]', 'NSF_ID': '000988542', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Mohammed', 'LastName': 'Albahttiti', 'PI_MID_INIT': 'T', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mohammed T Albahttiti', 'EmailAddress': '[email protected]', 'NSF_ID': '000731387', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Brendan', 'LastName': 'Coakley', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Brendan Coakley', 'EmailAddress': '[email protected]', 'NSF_ID': '000988711', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Marie', 'LastName': 'Patterson Feldstein', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Marie Patterson Feldstein', 'EmailAddress': '[email protected]', 'NSF_ID': '000986326', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Chico State Enterprises', 'CityName': 'CHICO', 'ZipCode': '959285388', 'PhoneNumber': '5308986811', 'StreetAddress': '25 MAIN ST UNIT 203', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'CA01', 'ORG_UEI_NUM': 'C4VMQLSU1LF4', 'ORG_LGL_BUS_NAME': 'CHICO STATE ENTERPRISES', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Chico State Enterprises', 'CityName': 'CHICO', 'StateCode': 'CA', 'ZipCode': '959285388', 'StreetAddress': '25 MAIN ST UNIT 203', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'CA01'}
|
{'Code': '285Y00', 'Text': 'EPIIC-Enbl Part Incr Innov Cap'}
|
2024~399998
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433215.xml'}
|
Collaborative Research: EPIIC: Cross-Continental Collaboration Coalition (C4)
|
NSF
|
09/01/2024
|
08/31/2027
| 400,000 | 400,000 |
{'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'}
|
The Cross-Continental Collaboration Coalition (C4) project is an interdisciplinary endeavor among five primarily undergraduate, four-year institutions—California State University, Chico; University of Central Oklahoma; Central Washington University; State University of New York (SUNY) Oswego; and Weber State University—to address the multifaceted challenges encountered in higher education today. One of the central challenges the investigators aim to tackle is the imperative to strengthen industry partnerships. Recognizing the pivotal role of industry collaboration in driving innovation and enhancing educational outcomes, each institution within the C4 cohort is committed to establishing and expanding regional innovation partnerships. These partnerships will serve as conduits for knowledge exchange, collaborative research projects, industry-informed curriculum realignment and experiential learning opportunities for students. By forging strong ties with industry stakeholders, the project seeks to ensure that educational programs at the C4 institutions remain relevant and responsive to the evolving needs of the workforce. Offering innovative programs tailored to meet the needs of employers, enhances the employability and career readiness of the C4 graduates. Another critical area of focus for the C4 project is the enhancement of research capacity. Robust research capabilities are essential for advancing knowledge, driving economic growth, and addressing pressing societal challenges. To this end, the C4 institutions are investing in research infrastructure, faculty development initiatives, and interdisciplinary collaboration platforms. By fostering a culture of innovation and inquiry, the investigators aim to position the C4 institutions as leaders in cutting-edge research and technology development. In addition to these institutional-level initiatives, the C4 project emphasizes cohort-wide collaboration and knowledge sharing. Through regular meetings, workshops, and joint initiatives, members of the C4 cohort exchange best practices, co-create innovative solutions, and support one another in achieving shared goals.<br/><br/>The C4 project emphasizes cohort-wide collaboration and knowledge sharing. Through regular meetings, workshops, and joint initiatives, members of the C4 cohort exchange best practices, co-create innovative solutions, and support one another in achieving shared goals. This project will contribute to the advancement of "best practices" in key areas of higher education and industry collaboration. Through collaborative efforts, participating institutions will identify and implement effective strategies for building vibrant regional innovation ecosystems and fostering interdisciplinary research and education. By leveraging the collective expertise of faculty and industry partners, the project will generate new knowledge, technologies, and approaches that can be adopted and replicated by other institutions facing similar challenges. Moreover, by integrating experiential learning opportunities and industry partnerships into academic programs, the project will enrich student learning experiences and prepare them for successful careers in dynamic and competitive fields. The potential impacts of the proposed project extend across multiple dimensions, including institutional, regional, and societal levels. At the institutional level, the project will enhance the reputation and competitiveness of participating institutions by strengthening their ties with industry partners and expanding their research capabilities. Additionally, by aligning academic programs with workforce needs, the project will enhance student outcomes and promote social mobility. The investigators expect this collaboration to impact the lives of 11,425 students annually. Regionally, the project will catalyze economic development by fostering innovation and entrepreneurship, creating job opportunities, and driving technological advancements. Furthermore, by promoting collaboration and knowledge sharing among institutions, the project will contribute to the broader landscape of higher education, inspiring innovation and excellence in teaching, research, and community engagement. Overall, the project will leave a lasting positive impact on participating institutions, their communities, and the higher education sector as a whole.<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.
|
07/29/2024
|
07/29/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2433216
|
[{'FirstName': 'Robert', 'LastName': 'Ogburn', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robert Ogburn', 'EmailAddress': '[email protected]', 'NSF_ID': '000990873', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Keke', 'LastName': 'Wu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Keke Wu', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A085B', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'William', 'LastName': 'Provaznik', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'William Provaznik', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A07X1', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Central Washington University', 'CityName': 'ELLENSBURG', 'ZipCode': '989267500', 'PhoneNumber': '5099632118', 'StreetAddress': '400 E UNIVERSITY WAY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Washington', 'StateCode': 'WA', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_ORG': 'WA08', 'ORG_UEI_NUM': 'SESUYWJGE3Y3', 'ORG_LGL_BUS_NAME': 'CENTRAL WASHINGTON UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Central Washington University', 'CityName': 'ELLENSBURG', 'StateCode': 'WA', 'ZipCode': '989267502', 'StreetAddress': '400 E UNIVERSITY WAY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Washington', 'CountryFlag': '1', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_PERF': 'WA08'}
|
{'Code': '285Y00', 'Text': 'EPIIC-Enbl Part Incr Innov Cap'}
|
2024~400000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433216.xml'}
|
Collaborative Research: EPIIC: Cross-Continental Collaboration Coalition (C4)
|
NSF
|
09/01/2024
|
08/31/2027
| 400,000 | 400,000 |
{'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'}
|
The Cross-Continental Collaboration Coalition (C4) project is an interdisciplinary endeavor among five primarily undergraduate, four-year institutions—California State University, Chico; University of Central Oklahoma; Central Washington University; State University of New York (SUNY) Oswego; and Weber State University—to address the multifaceted challenges encountered in higher education today. One of the central challenges the investigators aim to tackle is the imperative to strengthen industry partnerships. Recognizing the pivotal role of industry collaboration in driving innovation and enhancing educational outcomes, each institution within the C4 cohort is committed to establishing and expanding regional innovation partnerships. These partnerships will serve as conduits for knowledge exchange, collaborative research projects, industry-informed curriculum realignment and experiential learning opportunities for students. By forging strong ties with industry stakeholders, the project seeks to ensure that educational programs at the C4 institutions remain relevant and responsive to the evolving needs of the workforce. Offering innovative programs tailored to meet the needs of employers, enhances the employability and career readiness of the C4 graduates. Another critical area of focus for the C4 project is the enhancement of research capacity. Robust research capabilities are essential for advancing knowledge, driving economic growth, and addressing pressing societal challenges. To this end, the C4 institutions are investing in research infrastructure, faculty development initiatives, and interdisciplinary collaboration platforms. By fostering a culture of innovation and inquiry, the investigators aim to position the C4 institutions as leaders in cutting-edge research and technology development. In addition to these institutional-level initiatives, the C4 project emphasizes cohort-wide collaboration and knowledge sharing. Through regular meetings, workshops, and joint initiatives, members of the C4 cohort exchange best practices, co-create innovative solutions, and support one another in achieving shared goals.<br/><br/>The C4 project emphasizes cohort-wide collaboration and knowledge sharing. Through regular meetings, workshops, and joint initiatives, members of the C4 cohort exchange best practices, co-create innovative solutions, and support one another in achieving shared goals. This project will contribute to the advancement of "best practices" in key areas of higher education and industry collaboration. Through collaborative efforts, participating institutions will identify and implement effective strategies for building vibrant regional innovation ecosystems and fostering interdisciplinary research and education. By leveraging the collective expertise of faculty and industry partners, the project will generate new knowledge, technologies, and approaches that can be adopted and replicated by other institutions facing similar challenges. Moreover, by integrating experiential learning opportunities and industry partnerships into academic programs, the project will enrich student learning experiences and prepare them for successful careers in dynamic and competitive fields. The potential impacts of the proposed project extend across multiple dimensions, including institutional, regional, and societal levels. At the institutional level, the project will enhance the reputation and competitiveness of participating institutions by strengthening their ties with industry partners and expanding their research capabilities. Additionally, by aligning academic programs with workforce needs, the project will enhance student outcomes and promote social mobility. The investigators expect this collaboration to impact the lives of 11,425 students annually. Regionally, the project will catalyze economic development by fostering innovation and entrepreneurship, creating job opportunities, and driving technological advancements. Furthermore, by promoting collaboration and knowledge sharing among institutions, the project will contribute to the broader landscape of higher education, inspiring innovation and excellence in teaching, research, and community engagement. Overall, the project will leave a lasting positive impact on participating institutions, their communities, and the higher education sector as a whole.<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.
|
07/29/2024
|
07/29/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2433217
|
[{'FirstName': 'Mohammad', 'LastName': 'Islam', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mohammad A Islam', 'EmailAddress': '[email protected]', 'NSF_ID': '000658870', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Prabakar', 'LastName': 'Kothandaraman', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Prabakar Kothandaraman', 'EmailAddress': '[email protected]', 'NSF_ID': '000983155', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Hui', 'LastName': 'Zhang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hui Zhang', 'EmailAddress': '[email protected]', 'NSF_ID': '000792224', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Michele', 'LastName': 'Thornton', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michele Thornton', 'EmailAddress': '[email protected]', 'NSF_ID': '000986686', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Mohammad', 'LastName': 'Tajvarpour', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mohammad H Tajvarpour', 'EmailAddress': '[email protected]', 'NSF_ID': '000985400', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'SUNY College at Oswego', 'CityName': 'OSWEGO', 'ZipCode': '131263501', 'PhoneNumber': '3153122884', 'StreetAddress': '7060 STATE RTE 104', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '24', 'CONGRESS_DISTRICT_ORG': 'NY24', 'ORG_UEI_NUM': 'DLV5DEVHGF38', 'ORG_LGL_BUS_NAME': 'THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'SUNY at Oswego', 'CityName': 'OSWEGO', 'StateCode': 'NY', 'ZipCode': '131263501', 'StreetAddress': '7060 STATE RTE 104', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '24', 'CONGRESS_DISTRICT_PERF': 'NY24'}
|
{'Code': '285Y00', 'Text': 'EPIIC-Enbl Part Incr Innov Cap'}
|
2024~400000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433217.xml'}
|
Collaborative Research: EPIIC: Cross-Continental Collaboration Coalition (C4)
|
NSF
|
09/01/2024
|
08/31/2027
| 397,171 | 397,171 |
{'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'}
|
The Cross-Continental Collaboration Coalition (C4) project is an interdisciplinary endeavor among five primarily undergraduate, four-year institutions—California State University, Chico; University of Central Oklahoma; Central Washington University; State University of New York (SUNY) Oswego; and Weber State University—to address the multifaceted challenges encountered in higher education today. One of the central challenges the investigators aim to tackle is the imperative to strengthen industry partnerships. Recognizing the pivotal role of industry collaboration in driving innovation and enhancing educational outcomes, each institution within the C4 cohort is committed to establishing and expanding regional innovation partnerships. These partnerships will serve as conduits for knowledge exchange, collaborative research projects, industry-informed curriculum realignment and experiential learning opportunities for students. By forging strong ties with industry stakeholders, the project seeks to ensure that educational programs at the C4 institutions remain relevant and responsive to the evolving needs of the workforce. Offering innovative programs tailored to meet the needs of employers, enhances the employability and career readiness of the C4 graduates. Another critical area of focus for the C4 project is the enhancement of research capacity. Robust research capabilities are essential for advancing knowledge, driving economic growth, and addressing pressing societal challenges. To this end, the C4 institutions are investing in research infrastructure, faculty development initiatives, and interdisciplinary collaboration platforms. By fostering a culture of innovation and inquiry, the investigators aim to position the C4 institutions as leaders in cutting-edge research and technology development. In addition to these institutional-level initiatives, the C4 project emphasizes cohort-wide collaboration and knowledge sharing. Through regular meetings, workshops, and joint initiatives, members of the C4 cohort exchange best practices, co-create innovative solutions, and support one another in achieving shared goals.<br/><br/>The C4 project emphasizes cohort-wide collaboration and knowledge sharing. Through regular meetings, workshops, and joint initiatives, members of the C4 cohort exchange best practices, co-create innovative solutions, and support one another in achieving shared goals. This project will contribute to the advancement of "best practices" in key areas of higher education and industry collaboration. Through collaborative efforts, participating institutions will identify and implement effective strategies for building vibrant regional innovation ecosystems and fostering interdisciplinary research and education. By leveraging the collective expertise of faculty and industry partners, the project will generate new knowledge, technologies, and approaches that can be adopted and replicated by other institutions facing similar challenges. Moreover, by integrating experiential learning opportunities and industry partnerships into academic programs, the project will enrich student learning experiences and prepare them for successful careers in dynamic and competitive fields. The potential impacts of the proposed project extend across multiple dimensions, including institutional, regional, and societal levels. At the institutional level, the project will enhance the reputation and competitiveness of participating institutions by strengthening their ties with industry partners and expanding their research capabilities. Additionally, by aligning academic programs with workforce needs, the project will enhance student outcomes and promote social mobility. The investigators expect this collaboration to impact the lives of 11,425 students annually. Regionally, the project will catalyze economic development by fostering innovation and entrepreneurship, creating job opportunities, and driving technological advancements. Furthermore, by promoting collaboration and knowledge sharing among institutions, the project will contribute to the broader landscape of higher education, inspiring innovation and excellence in teaching, research, and community engagement. Overall, the project will leave a lasting positive impact on participating institutions, their communities, and the higher education sector as a whole.<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.
|
07/29/2024
|
07/29/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2433218
|
[{'FirstName': 'David', 'LastName': 'Ferro', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David Ferro', 'EmailAddress': '[email protected]', 'NSF_ID': '000662167', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'James', 'LastName': 'Taylor', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'James Taylor', 'EmailAddress': '[email protected]', 'NSF_ID': '000624575', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Benjamin', 'LastName': 'Garcia', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Benjamin W Garcia', 'EmailAddress': '[email protected]', 'NSF_ID': '000989931', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Weber State University', 'CityName': 'OGDEN', 'ZipCode': '844081014', 'PhoneNumber': '8016266055', 'StreetAddress': '3850 DIXON PKWY DEPT 1014', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Utah', 'StateCode': 'UT', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'UT01', 'ORG_UEI_NUM': 'ZAVDUCLBZG77', 'ORG_LGL_BUS_NAME': 'WEBER STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'ZAVDUCLBZG77'}
|
{'Name': 'Weber State University', 'CityName': 'OGDEN', 'StateCode': 'UT', 'ZipCode': '844081014', 'StreetAddress': '3850 DIXON PKWY DEPT 1014', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Utah', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'UT01'}
|
{'Code': '285Y00', 'Text': 'EPIIC-Enbl Part Incr Innov Cap'}
|
2024~397171
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433218.xml'}
|
EAGER: PBI: Measuring the impact of university innovation facilities through real estate market
|
NSF
|
09/01/2024
|
08/31/2026
| 285,504 | 285,504 |
{'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'}
|
Understanding the dynamics of Research and Development (R&D) space supply and demand can send crucial signals about the future performance of innovation ecosystems in America's metropolitan areas. This project seeks to assess whether the current supply of R&D space is aligned with anticipated demand forecasts across the top 100 U.S. metro areas. Additionally, identifying the locations of strong R&D concentrations, known as "innovation districts," is vital. These insights not only help predict innovation ecosystem performance but also influence investment decisions in innovation facilities. Such investments can impact the prices of adjacent real estate properties and signify the expansion of innovation capacity within these regions. By addressing these factors, this project aims to provide essential data for informed planning and strategic investment in R&D infrastructure, thereby supporting economic growth and technological advancement. <br/><br/>This project will develop answers to its research questions by collecting and analyzing data for four general outcome variables for top metropolitan statistical regions: (1) R&D space demand; (2) R&D space supply; (3) business establishment clustering; and (4) innovation district trade area density. Data collection will focus on the development of datasets that enable R&D facility forecasting and innovation district identification. The generation of R&D space demand and supply forecasts will follow the accounting-based market analysis methodology proposed by Mourouzi-Sivitanidou (2021). Innovation district-related data collection will use location data for firms in advanced industries in MSAs, enabling the measurement of clustering through Global Moran’s I values. Additionally, pre-anonymized mobile-based locational tracking data via Placer.ai will be used to study the trade area density (or, concentration) of visitors to innovation districts. The project will be conducted over the course of two years, during which dissemination of the generated data outputs and research papers will occur. The project’s main contributions will be to help address the lack of publicly available real estate market information about private R&D (research and development) space, and it will add to literature on innovation districts through the generation and analysis of novel datasets.<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
|
47.084
|
1
|
4900
|
4900
|
2433219
|
{'FirstName': 'Christopher', 'LastName': 'Smith', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christopher D Smith', 'EmailAddress': '[email protected]', 'NSF_ID': '000995817', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Southern Mississippi', 'CityName': 'HATTIESBURG', 'ZipCode': '394060001', 'PhoneNumber': '6012664119', 'StreetAddress': '118 COLLEGE DRIVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Mississippi', 'StateCode': 'MS', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MS04', 'ORG_UEI_NUM': 'M1K8LJAET5R1', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY OF SOUTHERN MISSISSIPPI', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Southern Mississippi', 'CityName': 'HATTIESBURG', 'StateCode': 'MS', 'ZipCode': '394060001', 'StreetAddress': '118 COLLEGE DRIVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Mississippi', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'MS04'}
|
{'Code': '301Y00', 'Text': 'NSF Engines - Type 2'}
|
2024~285504
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433219.xml'}
|
I-Corps: Translation potential of a mechanical tool to perform endoscopic vein harvesting
|
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 tool to reduce damage when harvesting veins used for coronary artery bypass grafting surgery. Heart disease is the leading cause of death in the U.S., with approximately 700,000 deaths annually from various heart conditions. Patients with coronary artery disease can suffer from unexpected heart attacks unless the blockages are removed or bypassed. Heart surgery carries significant costs for materials and tools that are currently used to harvest veins in the leg for coronary artery bypass surgery. Physician assistants and cardiothoracic surgeons have identified several issues using the current electrocautery devices on the market due to device failure during operation, added costs for the tool, added surgical time if bleeding occurs, and potential damage to the vein graft that can lead to poor outcomes after surgery. This solution has the potential to introduce a technology to reduce costs, surgical time, and damage to veins during harvesting.<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 a method to mechanically cut and clip veins during endovascular vein harvesting. To treat coronary artery disease patients, physicians perform a surgical procedure to replace a patient's damaged blood vessel with a suitable graft that is harvested from elsewhere in the body. The most common blood vessel used is the great saphenous vein in the leg. Harvesting is currently performed with electrocauterization tools that can cause unnecessary harm to the patient and result in poor patient outcomes. Electrocautery has been observed to fail to effectively seal the larger blood vessels while harvesting, damage tissue, and fail to cut through side vein branches. This technology is a purely mechanical tool that can cut through a blood vessel while clamping the side branches of veins shut. The tool is designed to provide physicians with a simpler, safer tool for harvesting procedures, which ultimately benefits the patients undergoing these procedures.<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
|
2433231
|
{'FirstName': 'Timothy', 'LastName': 'Chung', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Timothy K Chung', 'EmailAddress': '[email protected]', 'NSF_ID': '000859331', 'StartDate': '06/17/2024', 'EndDate': None, 'RoleCode': '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': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433231.xml'}
|
Collaborative Research: EPIIC: Rural AI Solutions and Engagement (RAISE)
|
NSF
|
08/01/2024
|
07/31/2027
| 380,000 | 380,000 |
{'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'}
|
The Rural AI Solutions and Engagement (RAISE) project is a collaboration between the University of Alaska Anchorage, Salisbury University, and Valdosta State University to build sustainable and strategic partnerships centered around Artificial Intelligence (AI) with industry, non-profit, indigenous, and government stakeholders in their respective regions. Each university serves a rural area in Alaska, Maryland, and Georgia, respectively. Rural communities face challenges such as limited technological infrastructure, educational resources, and access to rapidly evolving technology such as AI. This project addresses these challenges by building capacity at each institution to collaborate and partner with the community, strengthen research capabilities, and ultimately develop innovative AI solutions to rural problems.<br/><br/>The broad goals shared by the collaborating institutions are to develop capacity in (a) building partnerships, (b) research administration, (c) research development, and (d) research leadership. Utilizing these capacities, each institution will utilize AI to advance practical solutions in fields such as agriculture, energy, and education that are central to addressing community and rural needs in their region. Selected approaches include the creation of an Alaska AI Solutions Consortium that will integrate disparate AI efforts, solicit feedback from the community, and advance research through a mini-grant program; the launch of a Regional Partnership Incubator in the South Georgia community that will build a partner relationship management system and strengthen connections across the region to explore AI-driven solutions; and the construction of a new partnership inventory and research specialization for the rural areas of the Delmarva Peninsula that will feed into “AI for ALL” workshops and incentivize faculty participation in use-inspired research in AI. The cohort will also develop a perspective on rural AI innovation needs, share expertise and lessons learned, and explore future collaboration opportunities. As Predominantly Undergraduate Institutions (PUIs) and Minority Serving Institutions (MSIs), the participating institutions will also provide a technological boost to the workforce, especially among underrepresented populations.<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.
|
07/29/2024
|
07/29/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2433241
|
[{'FirstName': 'George', 'LastName': 'Kamberov', 'PI_MID_INIT': 'I', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'George I Kamberov', 'EmailAddress': '[email protected]', 'NSF_ID': '000206022', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Kenrick', 'LastName': 'Mock', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kenrick Mock', 'EmailAddress': '[email protected]', 'NSF_ID': '000461527', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Masoumeh', 'LastName': 'Heidari Kapourchali', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Masoumeh Heidari Kapourchali', 'EmailAddress': '[email protected]', 'NSF_ID': '000906506', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Alpana', 'LastName': 'Desai', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Alpana Desai', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A08CM', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Alaska Anchorage Campus', 'CityName': 'ANCHORAGE', 'ZipCode': '995084614', 'PhoneNumber': '9077861777', 'StreetAddress': '3211 PROVIDENCE DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Alaska', 'StateCode': 'AK', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'AK00', 'ORG_UEI_NUM': 'DZFJT2KH9C43', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ALASKA ANCHORAGE', 'ORG_PRNT_UEI_NUM': 'KNP1HA2B9BF8'}
|
{'Name': 'University of Alaska Anchorage Campus', 'CityName': 'ANCHORAGE', 'StateCode': 'AK', 'ZipCode': '995084614', 'StreetAddress': '3211 PROVIDENCE DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Alaska', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'AK00'}
|
{'Code': '285Y00', 'Text': 'EPIIC-Enbl Part Incr Innov Cap'}
|
2024~380000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433241.xml'}
|
Collaborative Research: EPIIC: Rural AI Solutions and Engagement (RAISE)
|
NSF
|
08/01/2024
|
07/31/2027
| 380,000 | 380,000 |
{'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'}
|
The Rural AI Solutions and Engagement (RAISE) project is a collaboration between the University of Alaska Anchorage, Salisbury University, and Valdosta State University to build sustainable and strategic partnerships centered around Artificial Intelligence (AI) with industry, non-profit, indigenous, and government stakeholders in their respective regions. Each university serves a rural area in Alaska, Maryland, and Georgia, respectively. Rural communities face challenges such as limited technological infrastructure, educational resources, and access to rapidly evolving technology such as AI. This project addresses these challenges by building capacity at each institution to collaborate and partner with the community, strengthen research capabilities, and ultimately develop innovative AI solutions to rural problems.<br/><br/>The broad goals shared by the collaborating institutions are to develop capacity in (a) building partnerships, (b) research administration, (c) research development, and (d) research leadership. Utilizing these capacities, each institution will utilize AI to advance practical solutions in fields such as agriculture, energy, and education that are central to addressing community and rural needs in their region. Selected approaches include the creation of an Alaska AI Solutions Consortium that will integrate disparate AI efforts, solicit feedback from the community, and advance research through a mini-grant program; the launch of a Regional Partnership Incubator in the South Georgia community that will build a partner relationship management system and strengthen connections across the region to explore AI-driven solutions; and the construction of a new partnership inventory and research specialization for the rural areas of the Delmarva Peninsula that will feed into “AI for ALL” workshops and incentivize faculty participation in use-inspired research in AI. The cohort will also develop a perspective on rural AI innovation needs, share expertise and lessons learned, and explore future collaboration opportunities. As Predominantly Undergraduate Institutions (PUIs) and Minority Serving Institutions (MSIs), the participating institutions will also provide a technological boost to the workforce, especially among underrepresented populations.<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.
|
07/29/2024
|
07/29/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2433242
|
[{'FirstName': 'Xiaohong', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xiaohong Wang', 'EmailAddress': '[email protected]', 'NSF_ID': '000632372', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Michael', 'LastName': 'Jensen', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michael Jensen', 'EmailAddress': '[email protected]', 'NSF_ID': '000988860', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Clifton', 'LastName': 'Griffin', 'PI_MID_INIT': 'P', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Clifton P Griffin', 'EmailAddress': '[email protected]', 'NSF_ID': '000570055', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Salisbury University', 'CityName': 'SALISBURY', 'ZipCode': '218016860', 'PhoneNumber': '4105436066', 'StreetAddress': '1101 CAMDEN AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'MD01', 'ORG_UEI_NUM': 'D69GS8RKHG25', 'ORG_LGL_BUS_NAME': 'SALISBURY UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Salisbury University', 'CityName': 'SALISBURY', 'StateCode': 'MD', 'ZipCode': '218016837', 'StreetAddress': '1101 CAMDEN AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'MD01'}
|
{'Code': '285Y00', 'Text': 'EPIIC-Enbl Part Incr Innov Cap'}
|
2024~380000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433242.xml'}
|
Collaborative Research: EPIIC: Rural AI Solutions and Engagement (RAISE)
|
NSF
|
08/01/2024
|
07/31/2027
| 379,867 | 379,867 |
{'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'}
|
The Rural AI Solutions and Engagement (RAISE) project is a collaboration between the University of Alaska Anchorage, Salisbury University, and Valdosta State University to build sustainable and strategic partnerships centered around Artificial Intelligence (AI) with industry, non-profit, indigenous, and government stakeholders in their respective regions. Each university serves a rural area in Alaska, Maryland, and Georgia, respectively. Rural communities face challenges such as limited technological infrastructure, educational resources, and access to rapidly evolving technology such as AI. This project addresses these challenges by building capacity at each institution to collaborate and partner with the community, strengthen research capabilities, and ultimately develop innovative AI solutions to rural problems.<br/><br/>The broad goals shared by the collaborating institutions are to develop capacity in (a) building partnerships, (b) research administration, (c) research development, and (d) research leadership. Utilizing these capacities, each institution will utilize AI to advance practical solutions in fields such as agriculture, energy, and education that are central to addressing community and rural needs in their region. Selected approaches include the creation of an Alaska AI Solutions Consortium that will integrate disparate AI efforts, solicit feedback from the community, and advance research through a mini-grant program; the launch of a Regional Partnership Incubator in the South Georgia community that will build a partner relationship management system and strengthen connections across the region to explore AI-driven solutions; and the construction of a new partnership inventory and research specialization for the rural areas of the Delmarva Peninsula that will feed into “AI for ALL” workshops and incentivize faculty participation in use-inspired research in AI. The cohort will also develop a perspective on rural AI innovation needs, share expertise and lessons learned, and explore future collaboration opportunities. As Predominantly Undergraduate Institutions (PUIs) and Minority Serving Institutions (MSIs), the participating institutions will also provide a technological boost to the workforce, especially among underrepresented populations.<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.
|
07/29/2024
|
07/29/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2433243
|
[{'FirstName': 'Darrell', 'LastName': 'Moore', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Darrell Moore', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A097M', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Zhiguang', 'LastName': 'Xu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zhiguang Xu', 'EmailAddress': '[email protected]', 'NSF_ID': '000989858', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Krishnendu', 'LastName': 'Roy', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Krishnendu Roy', 'EmailAddress': '[email protected]', 'NSF_ID': '000568833', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Radu', 'LastName': 'Mihail', 'PI_MID_INIT': 'P', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Radu P Mihail', 'EmailAddress': '[email protected]', 'NSF_ID': '000869023', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Valdosta State University', 'CityName': 'VALDOSTA', 'ZipCode': '316980001', 'PhoneNumber': '2293337837', 'StreetAddress': '1500 N PATTERSON ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_ORG': 'GA08', 'ORG_UEI_NUM': 'UHCVCJL7RWV3', 'ORG_LGL_BUS_NAME': 'VALDOSTA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Valdosta State University', 'CityName': 'VALDOSTA', 'StateCode': 'GA', 'ZipCode': '316980001', 'StreetAddress': '1500 N PATTERSON ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_PERF': 'GA08'}
|
{'Code': '285Y00', 'Text': 'EPIIC-Enbl Part Incr Innov Cap'}
|
2024~379867
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433243.xml'}
|
WORKSHOP: The 2024 XR Access Symposium
|
NSF
|
06/01/2024
|
05/31/2025
| 49,972 | 49,972 |
{'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': 'Ephraim Glinert', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924341'}
|
The XR Access 2024 Symposium will convene researchers and other stakeholders in the area of accessibility and XR to share research and devise a plan for making these technologies accessible to persons with disabilities. This funding will support attendees from academic institutions and nonprofit groups whose work touches accessibility and XR (collectively mixed, augmented, virtual, and extended reality, and 360 video). This year's event, to be held at Cornell Tech's Verizon Executive Education Center in New York City on June 6-7, 2024 builds on work begun at the 2019 Symposium that brought together over 120 researchers, advocates, and industry leaders to discuss the state of XR accessibility and plan for a more accessible future, and is the sixth in the series. The scope of the 2024 Symposium spans the content creation, software development, and hardware aspects of the XR industry, and it is a key aspect of the XR Access Initiative which aims to address the needs of users with speech, motor, vision, hearing and age-related impairments, with cognitive limitations, and with emotional and learning disabilities. There are currently 27 million Americans with low vision, 41 million who are Deaf or hard of hearing, and 18 million with limited mobility. For many of these people, using XR devices and consuming XR content is not possible. The research, design, and advocacy needed to include these users in the 18-billion-dollar XR market is still nascent. This Symposium will have broad impact by catalyzing new research into the specific mechanisms for improving XR accessibility. It will also serve to connect scientists to advocates, educators, and business leaders to ensure that advances in the science of accessibility are implemented with input from people with disabilities and are viable at scale. Persons with disabilities from academia and nonprofits will be encouraged to attend, because no conversation about increasing accessibility in technology can go forward in a meaningful manner without including disability advocates and users with disabilities at the table from the beginning.<br/><br/>XR technologies are on the cusp of becoming mainstream. They will soon reshape the way we work, learn and play. However, today XR technologies are not accessible to the millions of people with disabilities around the world. By their nature, they introduce a completely new set of challenges for people whose abilities are not typically considered in the technology design process. The Symposium will stimulate discussion and collaborative research to address questions such as: How can people with different perceptual abilities experience XR applications? How should XR hardware be designed to consider the needs of people with different abilities? What accessibility features can enhance immersion, enjoyment, and learning through XR for all users? The Symposium will also address deeper questions about the nature and future of accessibility for emerging technologies more broadly. Unlike prior work that develops assistive technology in XR to support people with disabilities, the Symposium aims to foster research that makes XR technologies themselves accessible. To ensure the impact of the research begun at the Symposium, the event's agenda will include meetings of cross-industry working groups, each focusing on increasing the XR Access Initiative's impact in a specific area. The Guidelines and Practices group will synthesize existing accessibility policies and practices in the XR space, and create new ones that are applicable to other emerging technologies. Similarly, the Outreach group will focus on creating strategies for bringing awareness of the need for XR accessibility to key corporate stakeholders and to the general public.<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
|
47.070
|
1
|
4900
|
4900
|
2433251
|
{'FirstName': 'Shiri', 'LastName': 'Azenkot', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shiri Azenkot', 'EmailAddress': '[email protected]', 'NSF_ID': '000690878', 'StartDate': '05/29/2024', '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': '736700', 'Text': 'HCC-Human-Centered Computing'}
|
2024~49972
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433251.xml'}
|
Collaborative Research: SBP: Understanding the Cultural and Psychological Roots of Inequality Maintenance: Omissions of Native Americans
|
NSF
|
01/01/2024
|
04/30/2025
| 593,719 | 407,145 |
{'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': 'Steven Breckler', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927369'}
|
Compared to other racial groups, Native Americans (the Indigenous Peoples of the United States) face disproportionately negative outcomes across many consequential domains of life, including education, income, housing, and criminal justice. Social psychology helps to understand how biases such as stereotyping, prejudice, and discrimination contribute to Native Americans’ disparate outcomes. This research team has identified another distinct form of bias that undermines Native Americans’ opportunities and wellbeing: biases of omission. Biases of omission refer to the ways in which Native Americans are written out of public consciousness. For example, research demonstrates that relative to other groups, mainstream television and news media rarely include Native People or discuss Native issues. Americans are also taught relatively little -- and largely inaccurate -- information about Native Americans. As one example, the majority of history curricula in American schools discuss Native Peoples only in pre-20th century contexts, rendering invisible the 5.2 million Native Americans currently living in the United States. The research in this project documents the scope and psychological impact of Native omissions, and explores how non-Native Americans justify those omissions. Studies also examine the motivational underpinnings of the relation between justifications of Native omissions and non-Natives’ national esteem, and test the efficacy of interventions that offer potential for improving Native peoples’ wellbeing.<br/> <br/>This project explores both the scope of biases of omissions of Native Americans and the psychological processes that perpetuate these biases. The research is based on the observation that a core cultural narrative of the United States is that of an exceptional, morally superior, equitable, and meritocratic society. Yet Native Peoples’ historic and contemporary experiences in the United States, including state-sanctioned violence and discrimination arising from the country’s settler colonial origins, contradicts these core cultural narratives. It is therefore hypothesized that Native omissions arise from a desire among non-Native Americans to protect these core cultural narratives and to maintain national esteem -- a sense of attachment to and pride in one’s nation. Three lines of studies test the tenets of this theoretical framework using large samples of Native American participants coupled with samples of non-Native adults from across the United States. The first phase of research documents the scope and psychological impact of Native omissions, including assessments of how and in what domains Native People experience omissions in U.S. society and the effect of omissions on individual and community wellbeing. Additional studies explore how and to what extent non-Native Americans justify omissions documented by Native participants, and whether justifications of Native omissions play a culturally protective role for non-Natives. The final phase of research examines the efficacy of acknowledging Native omissions as a means of improving Native peoples’ wellbeing by examining whether acknowledgements (vs. justifications) of Native omissions by mainstream U.S. institutions can enhance Native Americans’ individual and collective wellbeing. The program of research aims to expand the psychological literature by laying the theoretical groundwork for understanding an understudied form of bias and by shedding light on the experiences of Native Americans -- people who are vastly underrepresented in psychological theory and research. The project also documents and helps to change the psychological processes that perpetuate social inequalities, particularly those experienced by Native Americans, thereby contributing to the science of broadening participation.<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.
|
05/31/2024
|
05/31/2024
|
None
|
Grant
|
47.075
|
1
|
4900
|
4900
|
2433253
|
{'FirstName': 'Stephanie', 'LastName': 'Fryberg', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Stephanie Fryberg', 'EmailAddress': '[email protected]', 'NSF_ID': '000699620', 'StartDate': '05/31/2024', 'EndDate': None, 'RoleCode': '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': '110Y00', 'Text': 'SBP-Science of Broadening Part'}, {'Code': '133200', 'Text': 'Social Psychology'}]
|
2021~407145
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433253.xml'}
|
EAGER: Engineering preeclamptic trophoblast spheroid models to investigate placental cell invasion
|
NSF
|
10/01/2024
|
09/30/2026
| 259,570 | 259,570 |
{'Value': 'Standard Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Stephanie George', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927825'}
|
The placenta is a critical temporary organ that develops during pregnancy impacting lifelong health of both mother and infant. Many pregnancy-related complications are the result of a placental abnormality, including preeclampsia. Preeclampsia is a condition often clinically diagnosed by the onset of high blood pressure after the 20th week of pregnancy, which can necessitate preterm delivery. Preeclampsia occurs in 1 out of 12 pregnancies resulting in 76,000 maternal deaths and 500,000 infant deaths each year worldwide. Understanding and treating preeclampsia is challenging because the placenta is also one of the least understood human organs. The proposed work focuses on developing new 3D models using placental cells acquired after delivery from patients with preeclampsia. In addition, the proposed work includes research opportunities for undergraduate and high school students to engage in the project. The PI’s lab will also lead biomaterials outreach activities, particularly showing how biomaterials are advancing women’s health, with middle and high school students through local services that provide after and out-of-school activities.<br/><br/>Preeclampsia is a disease state of the placenta, an organ that is not well understood, necessitating new model systems to study it. Trophoblast cells are the main cell type composing the placenta, with important roles including nutrient and waste transport as well as invading the decidualized endometrium. There are few in vitro cell models available for preeclampsia, and currently there are no 3D in vitro systems using patient-derived preeclamptic trophoblast cells. The goal of the this project is to develop a preeclamptic trophoblast 3D spheroid model that enables studies of trophoblast invasiveness, a critical process for overall placental health. In Objective 1, preeclamptic trophoblast spheroid models will be developed and characterized. The spheroids will be incorporated within extracellular matrices mimicking the maternal endometrium. In Objective 2, the preeclamptic spheroid models will be used to investigate trophoblast cell invasion at the placental-endometrial interface. Comparisons will be made between spheroids developed using trophoblasts from either healthy patients or patients with diagnosed preeclampsia. The engineering advances of the proposed work include (1) Designing the appropriate culture conditions to develop spheroids that can be readily maintained and are repeatable, (2) Engineering the interface between the placenta and maternal endometrium by incorporating the spheroids within a methacrylated gelatin (GelMa) matrix, and (3) Developing the matrix composition and stiffness representative of the endometrium during pregnancy while also maintaining preeclamptic spheroid viability over time.<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
|
2433264
|
{'FirstName': 'Christina', 'LastName': 'Bailey-Hytholt', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christina M Bailey-Hytholt', 'EmailAddress': '[email protected]', 'NSF_ID': '000856356', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Worcester Polytechnic Institute', 'CityName': 'WORCESTER', 'ZipCode': '016092247', 'PhoneNumber': '5088315000', 'StreetAddress': '100 INSTITUTE RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'MA02', 'ORG_UEI_NUM': 'HJNQME41NBU4', 'ORG_LGL_BUS_NAME': 'WORCESTER POLYTECHNIC INSTITUTE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Worcester Polytechnic Institute', 'CityName': 'WORCESTER', 'StateCode': 'MA', 'ZipCode': '016092247', 'StreetAddress': '100 INSTITUTE RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'MA02'}
|
{'Code': '534500', 'Text': 'Engineering of Biomed Systems'}
|
2024~259570
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433264.xml'}
|
EFRI E3P: Sustainable and Circular Engineering for the Elimination of End-of-life Plastics: A Framework for Assessment, Design, and Innovation
|
NSF
|
10/01/2023
|
10/31/2025
| 2,000,000 | 1,150,098 |
{'Value': 'Standard Grant'}
|
{'Code': '07040000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'EFMA', 'LongName': 'Emerging Frontiers & Multidisciplinary Activities'}}
|
{'SignBlockName': 'Bruce Hamilton', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032920000'}
|
Engineering the Elimination of End-of-life Plastics (E3P) requires technological advances to maximize recycling and recovery, behavioral understanding to influence consumer attitudes, and economic approaches to incentivize extension of product life. Each alternative involves trade-offs in its social acceptability, economic feasibility, environmental sustainability, and circularity. For example, biodegradable plastics may seem to be most desirable if they decompose to become biological nutrients. However, if these materials have a large life cycle environmental impact, their adoption will not eliminate the end-of-life, but simply shift the environmental burden along the life cycle. Solutions for E3P need to be sustainable by being environmentally benign, economically feasible, and socially desirable. The overall goal of this project is to develop holistic and systematic methods and tools for assessment, design, and innovation toward Sustainable and Circular E3P (SCE3P). <br/><br/>The research team will conduct synergistic research in polymer chemistry, reaction engineering, and molecular simulation to determine properties of depolymerization and valorization processes under practical conditions of contamination; process design to model the cost and physical flows of current and emerging technologies; supply network modeling to determine the effects on the wider chemical industry; behavioral studies to discern and influence the role of consumers; and life cycle and circularity assessment to estimate environmental effects across global value chains. The resulting framework will consider the entire plastics life cycle, including thousands of combinations of alternatives at each step to select the "best" pathway. This framework will be able to assess existing products, design new products and pathways, and encourage innovation toward SCE3P. The framework will be useful for all types of plastics, but the project's experimental focus will be on polystyrene (PS) and poly(ethylene terepthalate) (PET) due to their large market. The SCE3P framework will be applied in the project to plastic products in the food service industry, with case studies done in collaboration with industry consortia and other stakeholders. The project is formulated to contribute to the convergence of chemical engineering, sustainable engineering, and behavioral science, for assessment, design, and innovation toward a sustainable and circular economy of plastics. A target is to develop new knowledge about the chemistry and engineering of various depolymerization and valorization approaches for PS and PET products. The research team will also bring together knowledge about steps in the plastics life cycle to contribute to an innovation roadmap for SCE3P. A spatial model of the U.S. chemical industry will be extended by including the plastics industry and emerging technologies for SCE3P. Behavioral studies will improve the understanding of spillover effects of other decisions on choice of plastic products and their responsible disposal. New data and methods will be developed for assessing and designing circular systems, evaluating their resilience, and identifying hotspots to focus innovation. Application to food services will guide progress toward goals of zero waste and carbon neutrality. The outcome of this project is to be a software prototype of the SCE3P framework, which will be disseminated widely via a university-based website, webinars to industry and other stakeholders, and university courses. Collaborators will provide access to over a hundred companies across the world. The team will develop teaching modules related to the research for inclusion in university courses and high school engineering curricula through the Engineer Your World program which reaches over 10,000 diverse high school students across the U.S.<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.
|
06/20/2024
|
06/20/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2433265
|
{'FirstName': 'Bhavik', 'LastName': 'Bakshi', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Bhavik R Bakshi', 'EmailAddress': '[email protected]', 'NSF_ID': '000107938', 'StartDate': '06/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Arizona State University', 'CityName': 'TEMPE', 'ZipCode': '852813670', 'PhoneNumber': '4809655479', 'StreetAddress': '660 S MILL AVENUE STE 204', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Arizona', 'StateCode': 'AZ', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'AZ04', 'ORG_UEI_NUM': 'NTLHJXM55KZ6', 'ORG_LGL_BUS_NAME': 'ARIZONA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Arizona State University', 'CityName': 'TEMPE', 'StateCode': 'AZ', 'ZipCode': '852813670', 'StreetAddress': '660 S MILL AVENUE STE 204', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Arizona', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'AZ04'}
|
{'Code': '763300', 'Text': 'EFRI Research Projects'}
|
2020~1150098
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433265.xml'}
|
E-CORE RII: Rhode Island Inclusive Network for Excellence in Science and Technology
|
NSF
|
09/01/2024
|
08/31/2028
| 7,992,646 | 2,034,790 |
{'Value': 'Cooperative Agreement'}
|
{'Code': '01060100', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OIA', 'LongName': 'OIA-Office of Integrative Activities'}}
|
{'SignBlockName': 'Jose Colom', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927088'}
|
Bolstered by thirteen Institutions of Higher Education, Rhode Island (RI) has long been an engine for scientific and technological innovation, from catalyzing the Industrial Revolution in 1790 to developing the first offshore wind farm in the U.S. in 2015. Continuing these institutions’ mission to enable a thriving, informed citizenry, this project will strengthen research infrastructure and capacity in RI, inclusive of the Narragansett Indian Tribe and its people. Led by the University of Rhode Island, Rhode Island College, Roger Williams University, Brown University, and the Rhode Island School of Design, the project will focus initially on building capacity in sciences related to RI’s blue economy. Once established, this network will further support life science and public health, energy, advanced materials, and food innovation and technology, aligning with the five research and workforce development themes in RI’s Science and Technology Plan. With research and educational facilities in close proximity, RI is emerging as an economic development leader in these areas. This project will position the state’s institutions, the Narragansett Indian Tribe, and government, community, and industry partners to sustain equitable, use-inspired research, as well as societal and economic growth into the future. The project has four main goals: 1) Strengthen workforce development by broadening research and education capacity; 2) Catalyze partnerships by seeding diverse and use-inspired research collaborations; 3) Strengthen science translation by implementing inclusive science communication; and 4) Provide for a robust administration of coordinated E-CORE and broader science and technology activity in the state. <br/><br/>The Rhode Island (RI) Inclusive Network for Excellence in Science and Technology (RII-NEST) project will enable RI and the Narragansett Indian Tribe (NIT) and its people to develop and maintain a sustainable, broadly inclusive, and competitive research ecosystem that supports use-inspired science & technology and workforce development. Project goals will be met through implementation of four research infrastructure cores: Administration, Workforce Development, Partnership, and Science Communications. These cores will develop and sustain a broadly inclusive and competitive research ecosystem that supports use-inspired S&T and workforce development. Led by the University of Rhode Island, in collaboration with Brown University, Rhode Island College (a Hispanic Serving Institution), Roger Williams University, and the Rhode Island School of Design, RII-NEST aligns with the strategic plans of participating institutions as well as state and federal priorities.The multi-institutional RII-NEST leadership team will collaborate with the RI Science and Technology Advisory Council (RI STAC), also serving as the RI EPSCoR Jurisdictional Steering Committee, to reinvigorate and grow the RI Research Alliance. RII-NEST will develop capacity, programming, platforms, and partnerships that sustain and grow over time. To reach this goal, RII-NEST will: 1) Institutionalize research infrastructure support programs that serve the whole jurisdiction; 2) Implement seed and planning grants that lead to the submission of collaborative proposals that strengthen and grow the S&T ecosystem; 3) Generate institutional and partner commitments that sustain key RII-NEST activities; and 4) Diversify the leadership, expertise, and benefit of RII-NEST programs and approaches across the jurisdiction by supporting primarily undergraduate institutions and the Narragansett Indian Tribe. This project is funded by the NSF EPSCoR Collaborations for Optimizing Research Ecosystems (E-CORE) RII Program. The E-CORE RII program supports jurisdictions in building capacity in one or more targeted research infrastructure cores that underlie the jurisdiction’s research ecosystem.<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
|
47.083
|
1
|
4900
|
4900
|
2433276
|
[{'FirstName': 'Jill', 'LastName': 'Pipher', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jill C Pipher', 'EmailAddress': '[email protected]', 'NSF_ID': '000231483', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Anabela', 'LastName': 'Resende da Maia', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Anabela M Resende da Maia', 'EmailAddress': '[email protected]', 'NSF_ID': '000657247', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jennifer', 'LastName': 'Bissonnette', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jennifer Bissonnette', 'EmailAddress': '[email protected]', 'NSF_ID': '000714369', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'James', 'LastName': 'Lemire', 'PI_MID_INIT': 'F', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'James F Lemire', 'EmailAddress': '[email protected]', 'NSF_ID': '000722994', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Elin', 'LastName': 'Torell', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Elin C Torell', 'EmailAddress': '[email protected]', 'NSF_ID': '000934265', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'University of Rhode Island', 'CityName': 'KINGSTON', 'ZipCode': '028811974', 'PhoneNumber': '4018742635', 'StreetAddress': '75 LOWER COLLEGE RD RM 103', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Rhode Island', 'StateCode': 'RI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'RI02', 'ORG_UEI_NUM': 'CJDNG9D14MW7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF RHODE ISLAND', 'ORG_PRNT_UEI_NUM': 'NSA8T7PLC9K3'}
|
{'Name': 'University of Rhode Island', 'CityName': 'KINGSTON', 'StateCode': 'RI', 'ZipCode': '028811974', 'StreetAddress': '75 LOWER COLLEGE RD RM 103', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Rhode Island', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'RI02'}
|
{'Code': '270Y00', 'Text': 'EPSCoR CORE RII'}
|
2024~2034790
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433276.xml'}
|
Collaborative Research: HCC: Medium: Computational Design of Complex Fluidic Systems
|
NSF
|
10/01/2023
|
09/30/2025
| 400,000 | 266,273 |
{'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': 'Ephraim Glinert', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924341'}
|
Recent advances in digital fabrication and computational design optimization have created a new paradigm for how efficiently components of structures, vehicles and wearable devices can be imagined, prototyped and deployed. An additional opportunity for high-impact innovation stems from the plethora of devices incorporating both solid and fluid components that human engineers have traditionally crafted relying on experience and established designed practices; examples include jet engines, hydraulic pumps, filtration systems and medical implants such as heart valves and coronary stents, all of which rely on a delicate functional interaction between a solid, often elastic, structure and a fluid medium. This project will leverage research momentum and experience from computational design optimization of purely solid, elastic structures (that have been the dominant focus of such techniques until now), to extend the reach of optimization-driven design to fluid- and flow-modulating mechanisms. Project outcomes will ultimately fuel innovation in energy efficiency, boost the functionality of soft robotic platforms, and enable the creation of next-generation microfluidic mechanisms including in highly effective prosthetics. Additional broad impact for project outcomes will derive from the development of exciting new curricula at the host institutions, while the real-world appeal and applications will provide strong outreach opportunities to K-12 and community colleges that attract students to STEM careers.<br/><br/>This research focuses on a number of specific challenges associated with functional devices that incorporate fluidic components. Non-linearity of both the solid/compliant phase and the dynamics of the fluid flow is highly relevant to such design tasks and will be treated as an integral component of algorithmic exploration. Non-parametric design approaches that are free to create accurate geometric details and intricate topological features will be explored, and the design of dynamic systems that include periodic or chaotic motion or flow, in conjunction with transient contact/collision patterns, will be investigated. The work will build on the PIs' prior products and expertise in delivering computational design frameworks that can handle tens or hundreds of millions of degrees of freedom, so that project outcomes can accommodate the specification of multiple design objectives stemming from multiple flow scenarios and/or multiple functional traits that contribute to the overall design. The research will develop methods and a scalable computational framework that jointly address these challenges, which is essential to delivering an effective and versatile design platform for fluidic mechanisms.<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.
|
05/20/2024
|
05/20/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2433307
|
{'FirstName': 'Bo', 'LastName': 'Zhu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Bo Zhu', 'EmailAddress': '[email protected]', 'NSF_ID': '000786907', 'StartDate': '05/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Georgia Tech Research Corporation', 'CityName': 'ATLANTA', 'ZipCode': '303186395', 'PhoneNumber': '4048944819', 'StreetAddress': '926 DALNEY ST NW', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'GA05', 'ORG_UEI_NUM': 'EMW9FC8J3HN4', 'ORG_LGL_BUS_NAME': 'GEORGIA TECH RESEARCH CORP', 'ORG_PRNT_UEI_NUM': 'EMW9FC8J3HN4'}
|
{'Name': 'Georgia Tech Research Corporation', 'CityName': 'ATLANTA', 'StateCode': 'GA', 'ZipCode': '303320315', 'StreetAddress': '926 DALNEY ST NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'GA05'}
|
{'Code': '736700', 'Text': 'HCC-Human-Centered Computing'}
|
2021~266273
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433307.xml'}
|
IRES Track I: Computational Co-Design of Physical Systems with Embodied Intelligence by Integrating Data, Simulation, and User Interface
|
NSF
|
10/01/2023
|
08/31/2025
| 299,964 | 224,710 |
{'Value': 'Standard Grant'}
|
{'Code': '01090000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OISE', 'LongName': 'Office Of Internatl Science &Engineering'}}
|
{'SignBlockName': 'Kristin Kuyuk', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924904'}
|
Designing embodied intelligence for physical systems is an emerging challenge in today's engineering and computing practices. This IRES project aims to tackle the challenge on both sides of software infrastructure creation to bridge scientific communities and research training curriculum development to educate STEM students. By collaborating with two user interface research groups at the University of Tokyo and Japan Advanced Institute of Science and Technology (JAIST), we bring together an interdisciplinary team with their complementary expertise in physics simulation, digital fabrication, data science, and human-computer interaction to devise novel computational tools to support the interactive design of intelligence-embodied physical systems. Fifteen U.S. students, both graduates and undergraduates, will visit Japan in the summer and jointly lead the research project by working with their collaborators at the University of Tokyo and JAIST. The three-month study and research experience will immerse the students in a unique research environment to develop their scientific understanding and programming practices to address the frontier research problems crossing artificial intelligence (AI), scientific computing, user interface, and computational design. The follow-up mentoring activities will guide the students' self-motivated exploration and future professional development in this interdisciplinary field.<br/> <br/>The overarching goal of this research project is to build an open-source software framework to lower the barriers for students, researchers, and engineers to conduct interactive design and visual programming of data-driven intelligent algorithms for various customizable physical systems, including examples of soft-bodied robots, drones, and materials. On the side of infrastructure development, we aim to democratize the creation of adaptable AI algorithms in specific physical and engineering contexts by providing an easy-to-access software framework to help designers conduct their data-integrated design tasks across engineering and computing communities. The software's architecture consists of three essential components --- frontend design interface, backend physics simulator, and data-driven physical-intelligent coordination --- which naturally transition to fifteen clustered sub-projects for the IRES students. On the side of research training development, we plan to redefine the standard way of problem-solving in physical intelligence by transitioning the workflow from the traditional data collection and model activity to a fully integrated design loop by interactively co-designing the data model, physical principles, and intelligent algorithms. We plan to train an inclusive group of students, with a particular focus on minorities and underrepresented students, by developing their new skillsets through developing this open-source infrastructure crossing physical and data sciences.<br/><br/>This project is jointly funded by the International Research Experience for Students program and the Established Program to Stimulate 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.
|
05/31/2024
|
05/31/2024
|
None
|
Grant
|
47.079, 47.083
|
1
|
4900
|
4900
|
2433313
|
{'FirstName': 'Bo', 'LastName': 'Zhu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Bo Zhu', 'EmailAddress': '[email protected]', 'NSF_ID': '000786907', 'StartDate': '05/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Georgia Tech Research Corporation', 'CityName': 'ATLANTA', 'ZipCode': '303186395', 'PhoneNumber': '4048944819', 'StreetAddress': '926 DALNEY ST NW', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'GA05', 'ORG_UEI_NUM': 'EMW9FC8J3HN4', 'ORG_LGL_BUS_NAME': 'GEORGIA TECH RESEARCH CORP', 'ORG_PRNT_UEI_NUM': 'EMW9FC8J3HN4'}
|
{'Name': 'Georgia Tech Research Corporation', 'CityName': 'ATLANTA', 'StateCode': 'GA', 'ZipCode': '303320415', 'StreetAddress': '926 DALNEY ST NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'GA05'}
|
[{'Code': '772700', 'Text': 'IRES Track I: IRES Sites (IS)'}, {'Code': '915000', 'Text': 'EPSCoR Co-Funding'}]
|
2022~224710
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433313.xml'}
|
EAGER: CI PAOS: FAIR Samples: exploring research and sample data management best practices in place-based research
|
NSF
|
08/01/2024
|
07/31/2026
| 297,966 | 297,966 |
{'Value': 'Standard Grant'}
|
{'Code': '05090000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'OAC', 'LongName': 'Office of Advanced Cyberinfrastructure (OAC)'}}
|
{'SignBlockName': 'Plato Smith', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924278'}
|
Field stations represent crucial sites where the application of FAIR (Findable, Accessible, Interoperable, and Reusable) principles—concepts designed to improve metadata preparation and ensure that research data is both discoverable and interoperable—can significantly impact local communities by advancing research and innovation. These stations are essential for collecting primary data across various disciplines and present a unique opportunity to enhance community development through improved research practices. One of the primary challenges in field-based research is the efficient management of physical samples, which is vital for data integrity and the integration of different data types. This project has identified significant inefficiencies in how samples are cataloged and managed at these stations, affecting data retention and quality, as well as the integration of sample data with experimental data in adherence to FAIR principles.<br/><br/>A key challenge in field-based research is the efficient management of physical samples, crucial for data integrity and the integration of various data types. The "FAIR Samples" project aims to refine the process of managing these samples from the ground up, emphasizing the integration of FAIR principles into the existing workflows of researchers. The project will explore how a Persistent Identifier (PID)-enabled sample management system can interoperate with other research tools to streamline the entire sample lifecycle.<br/><br/>This award by the Office of Advanced Cyberinfrastructure within the Directorate for Computer and Information Science and Engineering is jointly supported by the Division of Research, Innovation, Synergies, and Education within the 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.
|
07/31/2024
|
07/31/2024
|
None
|
Grant
|
47.050, 47.070
|
1
|
4900
|
4900
|
2433320
|
{'FirstName': 'John', 'LastName': 'Chodacki', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'John Chodacki', 'EmailAddress': '[email protected]', 'NSF_ID': '000801180', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California, Office of the President, Oakland', 'CityName': 'OAKLAND', 'ZipCode': '946075201', 'PhoneNumber': '5109879850', 'StreetAddress': '1111 FRANKLIN ST FL 8', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'CA12', 'ORG_UEI_NUM': 'PKK5TD16N4H1', 'ORG_LGL_BUS_NAME': 'THE REGENTS OF THE UNIVERSITY OF CALIFORNIA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'The Regents of University of California, Office of the President', 'CityName': 'OAKLAND', 'StateCode': 'CA', 'ZipCode': '946075201', 'StreetAddress': '1111 FRANKLIN ST FL 11', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'CA12'}
|
{'Code': '741400', 'Text': 'NSF Public Access Initiative'}
|
2024~297966
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433320.xml'}
|
Conference: CI PAOS: Advancing Research Data Management through Enhanced Vertical Interoperability
|
NSF
|
08/01/2024
|
07/31/2025
| 87,175 | 87,175 |
{'Value': 'Standard Grant'}
|
{'Code': '05090000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'OAC', 'LongName': 'Office of Advanced Cyberinfrastructure (OAC)'}}
|
{'SignBlockName': 'Plato Smith', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924278'}
|
This workshop aims to advance research data management by deepening understanding and implementation of vertical interoperability among varied digital tools across the research data lifecycle. The workshop's goal is to identify and overcome barriers to interoperability between tools that perform distinct functions yet are integral to managing data seamlessly from inception to archive. By bringing together experts and stakeholders, the aim to develop practical solutions and guidance to achieve comprehensive FAIR data practices.<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
|
2433321
|
{'FirstName': 'John', 'LastName': 'Chodacki', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'John Chodacki', 'EmailAddress': '[email protected]', 'NSF_ID': '000801180', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California, Office of the President, Oakland', 'CityName': 'OAKLAND', 'ZipCode': '946075201', 'PhoneNumber': '5109879850', 'StreetAddress': '1111 FRANKLIN ST FL 8', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'CA12', 'ORG_UEI_NUM': 'PKK5TD16N4H1', 'ORG_LGL_BUS_NAME': 'THE REGENTS OF THE UNIVERSITY OF CALIFORNIA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'The Regents of the University of California', 'CityName': 'OAKLAND', 'StateCode': 'CA', 'ZipCode': '946075201', 'StreetAddress': '1111 FRANKLIN ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'CA12'}
|
{'Code': '741400', 'Text': 'NSF Public Access Initiative'}
|
2024~87175
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433321.xml'}
|
Collaborative Research: HCC: Medium: Aerodynamic Virtual Human Simulation on Face, Body, and Crowd
|
NSF
|
10/01/2023
|
08/31/2027
| 383,000 | 383,000 |
{'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': 'Ephraim Glinert', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924341'}
|
This project develops the first high-fidelity aerodynamic virtual human model to support the scientific community and to tackle various emerging public-health problems. The proposed collaborative research addresses the significant and numerous computational challenges associated with the modeling and simulation of dynamic virtual human systems, involving aerodynamic flow processes and various physical components (e.g., face, hair, clothes, crowd, and thermal environments). The specific focus here is on modeling the human's aerodynamic micro-environment and its interactions with human respiratory activities, which have largely been neglected in the virtual human literature. The research aims are: (1) model the aerodynamic microenvironment consisting of thin layers of airflow near the boundary of human face; (2) simulate contact, friction, and solid-air coupling with areas of the human body, including skin, hair, and clothing surfaces; and (3) develop numerical algorithms to model aerodynamic crowds for multi-physics and multi-agent simulation. Among these aims, differentiable numerical solvers will be developed to facilitate optimization and computational design for human respiration-related problems.<br/><br/>The proposed algorithms will introduce a new family of computational tools based on first principles to fill the gaps in simulation, animation, design, and education regarding the previously ignored aerodynamic subarea of virtual human modeling. The PIs will also disseminate the results as open-source software libraries and databases of simulation results. If successful, the availability of these aerodynamics-aware virtual human models, augmented by an ensemble of differentiable physics simulators, individualized data models, interactive visualization, and VR/AR display, can provide convenient and intuitive tools for various applications that involve the human form.<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.
|
05/20/2024
|
05/20/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2433322
|
{'FirstName': 'Bo', 'LastName': 'Zhu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Bo Zhu', 'EmailAddress': '[email protected]', 'NSF_ID': '000786907', 'StartDate': '05/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Georgia Tech Research Corporation', 'CityName': 'ATLANTA', 'ZipCode': '303186395', 'PhoneNumber': '4048944819', 'StreetAddress': '926 DALNEY ST NW', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'GA05', 'ORG_UEI_NUM': 'EMW9FC8J3HN4', 'ORG_LGL_BUS_NAME': 'GEORGIA TECH RESEARCH CORP', 'ORG_PRNT_UEI_NUM': 'EMW9FC8J3HN4'}
|
{'Name': 'Georgia Tech Research Corporation', 'CityName': 'ATLANTA', 'StateCode': 'GA', 'ZipCode': '303320315', 'StreetAddress': '926 DALNEY ST NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'GA05'}
|
{'Code': '736700', 'Text': 'HCC-Human-Centered Computing'}
|
2023~383000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433322.xml'}
|
Travel: NSF Student Travel Grant for 2024 Formal Methods in Computer-Aided Design (FMCAD)
|
NSF
|
07/15/2024
|
06/30/2025
| 15,000 | 15,000 |
{'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': 'Pavithra Prabhakar', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922585'}
|
Formal Methods in Computer-Aided Design (FMCAD) 2024 is the twenty-fourth in a series of conferences on the theory and applications of formal methods in hardware and system verification. It provides a leading forum for researchers in academia and industry to present and discuss ground-breaking methods, technologies, theoretical results, and tools for reasoning formally about computing systems. This grant will help support conference travel for up to 8 students enrolled in US institutions to attend FMCAD, which will be in Prague, Czech Republic. The students will get the opportunity to present at the Student Forum, which is a platform for graduate students at any career stage to introduce their research to the wider formal methods research community and solicit feedback. <br/><br/>The field of formal methods is being rapidly deployed in a variety of areas both in academic research, as well as, in industrial systems. Thus, the broader significance and importance include fostering the next generation of researchers in this research area, as well as providing international experiences to build a globally aware workforce. In particular, students will have the opportunity to present at the Student Forum, learn state-of-the-art methodologies, be exposed to novel techniques, and interact with senior researchers in their areas of expertise. The organizers will give priority to students from under-represented groups and from universities without a formal methods 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.
|
07/12/2024
|
07/12/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2433324
|
{'FirstName': 'Clark', 'LastName': 'Barrett', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Clark Barrett', 'EmailAddress': '[email protected]', 'NSF_ID': '000423674', 'StartDate': '07/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Stanford University', 'CityName': 'STANFORD', 'ZipCode': '943052004', 'PhoneNumber': '6507232300', 'StreetAddress': '450 JANE STANFORD WAY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '16', 'CONGRESS_DISTRICT_ORG': 'CA16', 'ORG_UEI_NUM': 'HJD6G4D6TJY5', 'ORG_LGL_BUS_NAME': 'THE LELAND STANFORD JUNIOR UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Stanford University', 'CityName': 'STANFORD', 'StateCode': 'CA', 'ZipCode': '943052004', 'StreetAddress': '450 JANE STANFORD WAY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '16', 'CONGRESS_DISTRICT_PERF': 'CA16'}
|
{'Code': '779800', 'Text': 'Software & Hardware Foundation'}
|
2024~15000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433324.xml'}
|
Student Travel Support Program for the 63rd IEEE Conference on Decision and Control (CDC 2024)
|
NSF
|
08/01/2024
|
07/31/2025
| 20,000 | 20,000 |
{'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'}
|
This award will support students from institutions of higher learning in the United States to participate to the 63rd IEEE Conference on Decision and Control (CDC), to be held in Milan, Italy, December 16-19, 2024, along with pre-conference workshops to take place on December 15, 2024. The CDC has been for over fifty years the world’s leading annual forum for scientific and engineering researchers who share an interest in systems and control theory, and in the foundations of automation technology. As in the past, the 63rd IEEE CDC will feature an extensive program of contributed and invited papers, tutorial sessions, as well as plenary and semi-plenary sessions and workshops. The conference brings together academic and industrial researchers and students who share and explore their latest research ideas and discuss directions for future development of the field in light of current and anticipated developments in applications and technology. The range of topics covered at the annual CDC is extremely broad, mirroring the varied research threads and applications of control and systems theory. The system-theoretic approach has played a critical role in the development of many contemporary infrastructures and technologies affecting everyday life. Today, for example, system and control-theoretic tools are central in the design, operation, and security of cyber-physical systems, where they can inform researchers about ways to operate large networks (e.g., power, communications, computer, transportation, and health-related networks). Intensive study is also underway on the relationship of control theory and machine learning.<br/><br/>Students receiving travel funds from this award to attend the CDC will have many opportunities to interact with members of the professional community in a stimulating setting, and to exchange ideas with a broad group of professional colleagues. The large number of workshops before the conference and the interactive format of many of the presentations will allow additional opportunities for training, learning and for gaining experience in presenting technical results at a major professional conference. Special events will be arranged at the conference that focus on students and early career planning. Specific outreach efforts will be devoted to advertising the conference and the student travel award program to under-represented minorities.<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
|
47.041
|
1
|
4900
|
4900
|
2433335
|
{'FirstName': 'Philip', 'LastName': 'Pare', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Philip E Pare', 'EmailAddress': '[email protected]', 'NSF_ID': '000823877', 'StartDate': '07/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Purdue University', 'CityName': 'WEST LAFAYETTE', 'ZipCode': '479061332', 'PhoneNumber': '7654941055', 'StreetAddress': '2550 NORTHWESTERN AVE # 1100', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Indiana', 'StateCode': 'IN', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'IN04', 'ORG_UEI_NUM': 'YRXVL4JYCEF5', 'ORG_LGL_BUS_NAME': 'PURDUE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'YRXVL4JYCEF5'}
|
{'Name': 'Purdue University', 'CityName': 'WEST LAFAYETTE', 'StateCode': 'IN', 'ZipCode': '479061332', 'StreetAddress': '2550 NORTHWESTERN AVE # 1100', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Indiana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'IN04'}
|
{'Code': '760700', 'Text': 'EPCN-Energy-Power-Ctrl-Netwrks'}
|
2024~20000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433335.xml'}
|
2024 NSF Student Poster Competition and ME Rising Star Celebration at ASME International Mechanical Engineering Congress & Exposition (IMECE); Portland, Oregon; 17-21 November 2024
|
NSF
|
08/01/2024
|
07/31/2025
| 50,000 | 50,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Siddiq Qidwai', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922211'}
|
This grant provides travel support funds for undergraduate and graduate students and early career faculty to attend the 2024 ASME International Mechanical Engineering Congress and Exposition (ASME-IMECE) in Portland, Oregon, 17-21 November 2024. The travel funds will support 20 undergraduate and graduate students to present at a special poster session and 30 Assistant Professors to attend the ASME-IMECE and participate in the inaugural Mechanical Engineering Rising Star Celebration, expected to attract hundreds of participants. Both events will be open to all eligible conference attendees. The travel award selection will consider the inclusion of members from underrepresented groups and diversity of institutions represented by the students and faculty, and the variety of programs within engineering.<br/><br/>This grant aims to benefit the nation by educating a skilled and diverse engineering workforce prepared to provide transformative solutions to the challenges in their fields. Participant support is expected to enhance students' professional, scientific, and technical development as they present their NSF-funded research projects at the largest mechanical engineering conference in the nation. Students are expected to improve their communication skills through discussions of their work with top researchers. Participants will also have the chance to attend various technical presentations, keynote and plenary sessions featuring technological pioneers, and network with potential mentors, colleagues, and employers. For faculty, particularly untenured and underrepresented members, the conference provides a unique opportunity to network and form crucial connections with Rising Stars in Mechanical Engineering, offering long-term career benefits.<br/><br/>This project is funded by programs within the Division of Civil, Mechanical, and Manufacturing Innovations (CMMI) and the Division of Chemical, Bioengineering, Environmental and Transport Systems (CBET).<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
|
2433342
|
{'FirstName': 'Wenbin', 'LastName': 'Yu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Wenbin Yu', 'EmailAddress': '[email protected]', 'NSF_ID': '000494204', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Purdue University', 'CityName': 'WEST LAFAYETTE', 'ZipCode': '479061332', 'PhoneNumber': '7654941055', 'StreetAddress': '2550 NORTHWESTERN AVE # 1100', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Indiana', 'StateCode': 'IN', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'IN04', 'ORG_UEI_NUM': 'YRXVL4JYCEF5', 'ORG_LGL_BUS_NAME': 'PURDUE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'YRXVL4JYCEF5'}
|
{'Name': 'Purdue University', 'CityName': 'WEST LAFAYETTE', 'StateCode': 'IN', 'ZipCode': '479061332', 'StreetAddress': '2550 NORTHWESTERN AVE # 1100', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Indiana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'IN04'}
|
[{'Code': '058Y00', 'Text': 'M3X - Mind, Machine, and Motor'}, {'Code': '072Y00', 'Text': 'EDSE-Engineering Design and Sy'}, {'Code': '088Y00', 'Text': 'AM-Advanced Manufacturing'}, {'Code': '140600', 'Text': 'TTP-Thermal Transport Process'}, {'Code': '141500', 'Text': 'PMP-Particul&MultiphaseProcess'}, {'Code': '163000', 'Text': 'Mechanics of Materials and Str'}, {'Code': '229Y00', 'Text': 'MSI-Manufacturing Systms Integ'}, {'Code': '756900', 'Text': 'Dynamics, Control and System D'}]
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433342.xml'}
|
Conference: International Conference on Epigenetics & Bioengineering
|
NSF
|
07/15/2024
|
12/31/2024
| 33,400 | 33,400 |
{'Value': 'Standard Grant'}
|
{'Code': '08070000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'MCB', 'LongName': 'Div Of Molecular and Cellular Bioscience'}}
|
{'SignBlockName': 'Manju Hingorani', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927323'}
|
This award will support attendance by students and early career researchers at the 2024 International Conference on Epigenetics and Bioengineering (EpiBio) on October 3-5, 2024, at the Hotel Casa Amsterdam in Amsterdam, Netherlands. EpiBio explores fundamental research and cutting-edge technologies and applications related to the epigenome. The conference brings together interdisciplinary expertise in the field — allying biology, chemistry, physics, data science, and engineering to foster the development of novel methodologies and tools to answer biological questions in epigenetics. Attendees, including graduate students, post-docs, academic faculty, and industry professionals will have the opportunity to engage with peers and established international leaders in the field through keynote talks, oral and poster presentations, and networking activities.<br/><br/>The conference will focus on diverse areas of epigenetics and bioengineering. The main themes are organized around computational epigenetics, clinical epigenetics engineering, emerging technologies, perturbing chromatin and epigenetic engineering, sensing epigenetic modifications and single cell epigenetics. Support will be provided for a diverse group of graduate students, post-docs and early career faculty to attend the conference. These groups of people often do not have the financial resources to travel and participate in events that are important sources of ideas and feedback on research, and provide professional networking, collaboration and career development opportunities. Attendance at EpiBio 2024 will have substantive benefits for U.S.-based researchers starting their career because research in this field has historically been centered in Europe.<br/><br/>This award is co-funded by the Genetic Mechanisms and Systems and Synthetic Biology programs in the Division of Molecular and Cellular Biosciences of the Directorate for Biological Sciences, and the Cellular and Biochemical Engineering program in 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.
|
06/24/2024
|
06/24/2024
|
None
|
Grant
|
47.041, 47.074
|
1
|
4900
|
4900
|
2433351
|
{'FirstName': 'Evan', 'LastName': 'Flach', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Evan Flach', 'EmailAddress': '[email protected]', 'NSF_ID': '000662136', 'StartDate': '06/24/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'American Institute of Chemical Engineers', 'CityName': 'NEW YORK', 'ZipCode': '100055991', 'PhoneNumber': '6464951350', 'StreetAddress': '120 WALL ST', 'StreetAddress2': '23 FLO', 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'NY10', 'ORG_UEI_NUM': 'KLPNCLPDAS45', 'ORG_LGL_BUS_NAME': 'AMERICAN INSTITUTE OF CHEMICAL ENGINEERS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'American Institute of Chemical Engineers', 'CityName': 'NEW YORK', 'StateCode': 'NY', 'ZipCode': '100055991', 'StreetAddress': '120 WALL ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'NY10'}
|
[{'Code': '111200', 'Text': 'Genetic Mechanisms'}, {'Code': '149100', 'Text': 'Cellular & Biochem Engineering'}, {'Code': '801100', 'Text': 'Systems and Synthetic Biology'}]
|
2024~33400
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433351.xml'}
|
Materials-Manufacturing-Machine Learning Nexus (M3X) Conference: Athens, Georgia; 18-20 May 2025
|
NSF
|
10/01/2024
|
09/30/2025
| 30,000 | 30,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Khershed Cooper', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927017'}
|
This award provides participant support for students and young researchers to attend the Materials-Manufacturing-Machine Learning Nexus (M3X) Conference at the University of Georgia, Athens, Georgia, 18-20 May 2025. Priority is given to participation by women and underrepresented minority groups, which promotes diversity, equity, and inclusion. The M3X conference explores research at the intersection of materials science, manufacturing technologies, and machine learning. U.S. and international researchers, faculty and scholars present their research results on advanced materials, manufacturing and machine learning. The conference impacts the materials, manufacturing and data science communities through discussions of cutting-edge research. This project benefits the nation through the education of a skilled science and engineering workforce, which is better prepared to provide transformative solutions to the challenges in their chosen fields. The conference plays an important role in supporting and sustaining machine learning-enabled advanced material discovery and advanced manufacturing, which have various important applications in many industrial sectors such as microelectronics, energy, healthcare, automotive and aerospace.<br/><br/>This participant support is expected to benefit the students’ and young researchers’ professional, scientific, and technical development. Attendance at the conference gives the students and young faculty a broader view of advanced materials, manufacturing and machine learning technologies, their fundamentals and practical applications. The conference provides a venue for presentations and discussions on the integration of advanced computational methods with materials science and manufacturing engineering. Specifically, the discussions focus on using machine learning algorithms to optimize material properties, enhance manufacturing efficiencies, and streamline production processes. At the conference, concepts and challenges at the intersection of advanced materials, manufacturing and machine learning are identified and presented, and attendees chart new paths forward in the field and rally a new generation of researchers toward them. The conference is attended by U.S. and international researchers, which provides an opportunity for a variety of perspectives to be presented and discussed. The conference is an opportunity for participants to showcase their scientific accomplishments and interact with peers and colleagues in academia, government laboratories and industry.<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
|
2433352
|
{'FirstName': 'Kenan', 'LastName': 'Song', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kenan Song', 'EmailAddress': '[email protected]', 'NSF_ID': '000767374', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Georgia Research Foundation Inc', 'CityName': 'ATHENS', 'ZipCode': '306021589', 'PhoneNumber': '7065425939', 'StreetAddress': '310 E CAMPUS RD RM 409', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'GA10', 'ORG_UEI_NUM': 'NMJHD63STRC5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF GEORGIA RESEARCH FOUNDATION, INC.', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Georgia Research Foundation Inc', 'CityName': 'ATHENS', 'StateCode': 'GA', 'ZipCode': '306021589', 'StreetAddress': '310 E CAMPUS RD RM 409', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'GA10'}
|
{'Code': '088Y00', 'Text': 'AM-Advanced Manufacturing'}
|
2024~30000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433352.xml'}
|
Conference: Network and Distributed System Security Symposium 2024
|
NSF
|
07/15/2024
|
12/31/2024
| 20,000 | 20,000 |
{'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': 'Dan Cosley', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928832'}
|
This award provides funding to support about 20 U.S.-based students attending the 2024 Network and Distributed System Security (NDSS) Symposium, held in San Diego, California. The NDSS Symposium is an annual conference hosted by the Internet Society that provides a leading venue for cybersecurity experts and practitioners to present their latest work around researching, designing, developing, exploiting, and deploying the technologies that define network and distributed systems. Attendees include university researchers, educators, technology officers, industry experts, students, and corporate sponsors; this range of backgrounds will allow student attendees to interact with a wide variety of key actors in the network and distributed systems community. <br/><br/>Stronger Internet security is vital to the well-being of all Americans in today's society; the NDSS Symposium provides a leading venue for cybersecurity researchers and practitioners to exchange experiences and strengthen common approaches for safeguarding Internet security. Funding student attendees who would otherwise be financially unable to attend helps develop the next generation of talent. In particular, the NDSS Symposium seeks to bring underrepresented groups, such as youth and women, into the Internet security field to broaden the talent pool available to both cybersecurity research and practice. Students will be selected based on their evidence of interest, leadership, and collaboration around security-related topics; their financial need and benefits of attending for both themselves and the conference; and their ability to bring a wide variety of perspectives to the field.<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.
|
07/16/2024
|
07/16/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2433361
|
{'FirstName': 'Joseph', 'LastName': 'Hall', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Joseph L Hall', 'EmailAddress': '[email protected]', 'NSF_ID': '000981582', 'StartDate': '07/16/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Internet Society', 'CityName': 'RESTON', 'ZipCode': '201904744', 'PhoneNumber': '7034392120', 'StreetAddress': '11710 PLAZA AMERICA DR STE 400', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_ORG': 'VA11', 'ORG_UEI_NUM': 'JV1NMHVGBNV8', 'ORG_LGL_BUS_NAME': 'INTERNET SOCIETY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Internet Society', 'CityName': 'RESTON', 'StateCode': 'VA', 'ZipCode': '201904744', 'StreetAddress': '11710 PLAZA AMERICA DR STE 400', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_PERF': 'VA11'}
|
{'Code': '806000', 'Text': 'Secure &Trustworthy Cyberspace'}
|
2024~20000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433361.xml'}
|
E-CORE RII: Mississippi Research Alliance
|
NSF
|
09/01/2024
|
08/31/2028
| 8,000,000 | 4,494,633 |
{'Value': 'Cooperative Agreement'}
|
{'Code': '01060100', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OIA', 'LongName': 'OIA-Office of Integrative Activities'}}
|
{'SignBlockName': 'Casonya Johnson', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922658'}
|
This project establishes the Mississippi Research Alliance (MRA) as a nexus for the state’s research ecosystem, leveraging existing strengths, expanding networks, and creating new opportunities to enhance Mississippi’s research and development (R&D) competitiveness. With a focus on overcoming barriers to access and sustainability, MRA will mobilize the entire jurisdiction to bridge critical gaps, enhance physical infrastructure essential for academic-led R&D, and encourage partnerships that connect comprehensive research universities with Emerging Research Institutions, state agencies, and public and private organizations. MRA creates an inclusive R&D ecosystem by broadening opportunities, lowering entry barriers and ensuring a diverse group of researchers can contribute to scientific progress. The project bolsters the state’s technology-driven research enterprise by fostering a collaborative, multidisciplinary R&D ecosystem that can attract top scientific talent. Ultimately, this project will drive economic growth through scientific and technological advancements, making significant strides towards a knowledge-based economy that will improve the quality of life for Mississippi residents.<br/><br/>This project, led by Mississippi State University in partnership with Mississippi Valley State University, The University of Mississippi, and The University of Southern Mississippi, is overseen by the Mississippi EPSCoR jurisdictional steering committee (JSC). MRA’s vision is to be a transformative force in the Mississippi research and innovation ecosystem. MRA will forge strategic partnerships that harness and enhance existing human and physical assets and coordinate new investments to position Mississippi as a leader in science and technology, fostering an ecosystem where innovation thrives through collaboration. MRA efforts are divided into three cores: Strategic Governance, Sustainable Shared Instrumentation, and Administrative. The Strategic Governance Core will expand the JSC to enhance statewide resource coordination, accelerating economic growth grounded in scientific research and development. The Sustainable Shared Instrumentation Core will improve the impact and longevity of core facilities within the state by addressing existing barriers to access and sustainability and promoting the use of these facilities across Mississippi. The Administrative Core will cultivate and expand interdisciplinary team networks that foster effective collaboration and resource sharing to facilitate seamless knowledge exchange throughout the R&D ecosystem. This core will also use an expanded networking strategy to engage key individuals, groups, and organizations to amplify collaborative efforts supporting the MRA’s mission. These distinct but highly integrated cores will collectively address infrastructure gaps and integrate essential components to foster a thriving ecosystem. This will ensure Mississippi’s continued progress, competitiveness, and capacity to tackle the complex challenges facing our state and Nation. This project is funded by the NSF EPSCoR Collaborations for Optimizing Research Ecosystems (E-CORE) RII Program. The E-CORE RII program supports jurisdictions in building capacity in one or more targeted research infrastructure cores that underlie the jurisdiction’s research ecosystem.<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
|
47.083
|
1
|
4900
|
4900
|
2433435
|
[{'FirstName': 'Alex', 'LastName': 'Flynt', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Alex Flynt', 'EmailAddress': '[email protected]', 'NSF_ID': '000685676', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Nathan', 'LastName': 'Hammer', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nathan Hammer', 'EmailAddress': '[email protected]', 'NSF_ID': '000348847', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Tonia', 'LastName': 'Lane', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tonia Lane', 'EmailAddress': '[email protected]', 'NSF_ID': '000919644', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Victor', 'LastName': 'Bii', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Victor M Bii', 'EmailAddress': '[email protected]', 'NSF_ID': '000985634', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Katherine', 'LastName': 'Echols', 'PI_MID_INIT': 'I', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Katherine I Echols', 'EmailAddress': '[email protected]', 'NSF_ID': '000707792', 'StartDate': '08/19/2024', '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': '270Y00', 'Text': 'EPSCoR CORE RII'}
|
2024~4494633
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433435.xml'}
|
Travel: Travel Supplement for The Vison Workshop on Distributed Computing and Swarm Intelligence
|
NSF
|
07/01/2024
|
06/30/2025
| 25,000 | 25,000 |
{'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': 'Marilyn McClure', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032925197'}
|
The proposed travel grant aims to cover the expenses for United States (US) scholars attending the Vision Workshop on Distributed Computing and Swarm Intelligence, scheduled for June 24-26, 2024, in Sabaudia, near Rome, Italy. DISCOVER-US represents a pivotal collaboration between European Union (EU) and US research institutions, focusing on advancing distributed computing and swarm intelligence.<br/><br/>Intellectual Merit:<br/>This Vision Workshop on Distributed Computing and Swarm Intelligence will address the following research areas:<br/>o Managing complexity through high levels of abstraction;<br/>o Distributed computing, the compute continuum, swarm intelligence, and edge AI;<br/>o Self-organization, dynamic, and adaptive management; and<br/>o Collaborative programming frameworks and software development tools.<br/><br/>Broader Impacts:<br/>Reasons to support this request include providing the students with the opportunity to:<br/>o Interact with top researchers within their research domain;<br/>o Learn, listen, and exchange ideas with other experts and students working in their research domain to build future collaborations;<br/>o Learn what is considered state-of-the-art in design, implementation, analysis, evaluation, and deployment of computer systems and applications at the edge; and<br/>o Attend topic specific discussions.<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
|
47.070
|
1
|
4900
|
4900
|
2433479
|
{'FirstName': 'Yiran', 'LastName': 'Chen', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yiran Chen', 'EmailAddress': '[email protected]', 'NSF_ID': '000575362', 'StartDate': '06/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Duke University', 'CityName': 'DURHAM', 'ZipCode': '277054640', 'PhoneNumber': '9196843030', 'StreetAddress': '2200 W MAIN ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'NC04', 'ORG_UEI_NUM': 'TP7EK8DZV6N5', 'ORG_LGL_BUS_NAME': 'DUKE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Duke University', 'CityName': 'DURHAM', 'StateCode': 'NC', 'ZipCode': '277054640', 'StreetAddress': '2200 W MAIN ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'NC04'}
|
{'Code': '735400', 'Text': 'CSR-Computer Systems Research'}
|
2024~25000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433479.xml'}
|
CAREER: Dynamic Process-Attribute-Data-Performance Modeling to Enable Smart Ultrasonic Metal Welding
|
NSF
|
01/01/2024
|
01/31/2025
| 500,000 | 250,982 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Bruce Kramer', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032925348'}
|
This Faculty Early Career Development (CAREER) grant will support fundamental research on ultrasonic metal welding (UMW). Among the advantages of UMW over conventional fusion welding techniques are the ability to join dissimilar metals, energy efficiency, short welding cycles, and environmental friendliness, making it a promising joining technology for the advanced manufacturing of electrified and lightweight vehicles. Nevertheless, UMW has a relatively narrow operating window and is very sensitive to unpredictable, uncontrollable environmental conditions. This longstanding knowledge gap in the underlying process mechanisms makes the prediction and control of joint quality difficult, which limits its use. This project will take advantage of the emergent information-centric transformation of manufacturing science by leveraging advances in process physics, microstructural analysis, and data science. By establishing dynamic, stochastic relationships between process conditions, microstructural weld attributes, online sensing data, and weld performance, the research will advance the fundamental understanding of process mechanisms in UMW. The knowledge gained will be used to establish a suite of machine learning-based decision-making tools that will ultimately enable smart UMW. This grant will also support diverse educational and outreach activities that contribute to the education of the U.S. smart manufacturing workforce. <br/><br/>It is a widely accepted hypothesis that UMW process conditions influence the joining performance via the dynamic evolution of micro-scale weld attributes and the weld formation process generates a signature, as reflected in parameters that can be sensed online. Nonetheless, there exist no studies to date that adequately model or quantify the inherent dynamic, stochastic process-attribute-data-performance (PADP) relationship. The overarching goal of this research is to create a PADP modeling framework that consists of innovative machine learning and statistical models. The framework will be completed in two steps. First, spatiotemporal models incorporating uncertainty quantification will be built to characterize the process-attribute-performance relationship. Second, a tensor-based correlation and regression analysis will be performed to investigate the attribute-data relationship. This framework will be further employed to develop a series of physics-aware, machine learning tools for process control, including process optimization, online quality monitoring, and real-time control. Finally, the project will investigate the use of a transfer learning methodology to provide a cost-effective way to build PADP models and decision-making strategies for related products or product families. This learning capability will be an essential component in the cloud intelligence that enables the smart manufacturing paradigm.<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.
|
06/20/2024
|
06/20/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2433484
|
{'FirstName': 'Chenhui', 'LastName': 'Shao', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Chenhui Shao', 'EmailAddress': '[email protected]', 'NSF_ID': '000736003', 'StartDate': '06/20/2024', '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': 'ANN ARBOR, MI 481091079', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'MI06'}
|
[{'Code': '088Y00', 'Text': 'AM-Advanced Manufacturing'}, {'Code': '104500', 'Text': 'CAREER: FACULTY EARLY CAR DEV'}]
|
2020~250982
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433484.xml'}
|
Doctoral Dissertation Research: Enhancing Heat Risk Modeling for Spatially Targeted Interventions
|
NSF
|
10/01/2024
|
09/30/2026
| 30,150 | 30,150 |
{'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': 'May Yuan', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922206'}
|
Heat is a leading weather-related cause of deaths and illnesses globally, but most heat-related health outcomes are preventable. Policy-relevant targeted interventions based on hazard-specific vulnerability assessment can lead to improved disaster risk strategies. This project seeks to enhance heat vulnerability assessment for targeted responses to save lives and protect against preventable illnesses. The overriding research question is: how can hazard-specific, place-specific, and time-variant heat vulnerability representative variables enable spatially targeted interventions that are policy-relevant? The research is critical to advancing theories toward heat-specific and place-specific vulnerability representations. <br/><br/>Heat vulnerability studies typically use general, all-hazard conceptual models that provide broad frameworks for understanding various types of hazards. However, general conceptualizations do not sufficiently promote tailored heat-specific strategies, undermining effective responses. This project investigates the decision criteria underpinning heat vulnerability including the selection of input variables, modeling approaches, statistical considerations, and geospatial science issues, toward the development and refining of consistent theories and conceptual frameworks that are heat-specific and place-specific. This project works to develop a generalizable approach for testing hypotheses and theoretical frameworks of heat vulnerability, which is crucial for instituting mitigative and adaptive protections against preventable health outcomes. Knowledge gained from this research can inform local and federal agencies in the coordinating, planning, and implementing of heat relief activities, toward enhancing community resilience. The study findings contribute a basis for nationwide or global heat response activities, such as the placement of hydration stations, cooling centers, and personal heat relief resources.<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
|
47.075
|
1
|
4900
|
4900
|
2433486
|
[{'FirstName': 'Matei', 'LastName': 'Georgescu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Matei Georgescu', 'EmailAddress': '[email protected]', 'NSF_ID': '000565309', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Amy', 'LastName': 'Frazier', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Amy Frazier', 'EmailAddress': '[email protected]', 'NSF_ID': '000630843', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jennifer', 'LastName': 'Vanos', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jennifer K Vanos', 'EmailAddress': '[email protected]', 'NSF_ID': '000660805', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Joseph', 'LastName': 'Karanja', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Joseph Karanja', 'EmailAddress': '[email protected]', 'NSF_ID': '000993716', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Arizona State University', 'CityName': 'TEMPE', 'ZipCode': '852813670', 'PhoneNumber': '4809655479', 'StreetAddress': '660 S MILL AVENUE STE 204', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Arizona', 'StateCode': 'AZ', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'AZ04', 'ORG_UEI_NUM': 'NTLHJXM55KZ6', 'ORG_LGL_BUS_NAME': 'ARIZONA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Arizona State University', 'CityName': 'TEMPE', 'StateCode': 'AZ', 'ZipCode': '852813670', 'StreetAddress': '660 S MILL AVENUE STE 204', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Arizona', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'AZ04'}
|
{'Code': '160Y00', 'Text': 'HEGS-DDRI Human-Enviro&Geo Sci'}
|
2024~30150
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433486.xml'}
|
Conference: SACNAS GeoFutures
|
NSF
|
08/01/2024
|
07/31/2025
| 99,933 | 99,933 |
{'Value': 'Standard Grant'}
|
{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}
|
{'SignBlockName': 'Elizabeth Rom', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927709'}
|
Faculty and staff at the University of Washington (UW) will organize and lead Geo-Futures, a conference-based mentoring program housed within the SACNAS (Society for Advancing Hispanics/Chicanos and Native Americans in Science) 2025 annual Conference. The Geo-Futures program will provide student attendees with mentoring before, during and after their SACNAS experience to help them maintain the intellectual momentum acquired during their time at the conference. The program will help students develop a sense of identity and community within the geosciences and assist them as they begin to define their academic and professional pathways through the discipline. Setting GeoFutures within the annual SACNAS Conference also allows for engagement with the cultural value structures of the many students participating in the program. GeoFutures will use previously developed engagement strategies for recruiting and retaining the diverse assemblage of students and perspectives that will be required to address the emerging workforce needs of 21st century geoscience.<br/><br/>GEO-Futures offers students pre and post-conference training that will prepare them to participate in a national scientific research conference. Pre-conference activities will provide students with an introduction on navigating a scientific conference and networking with geoscientists in attendance. Conference activities will provide students with an introduction to original research being conducted in the geosciences and examples of career pathways that can be engaged in as a professional geoscientist. Beyond providing students with guidance on how to pursue academic and professional careers in geoscience, the Geo-Futures program can help them understand how their diverse talents and perspectives can contribute to a scientific workforce that will be called upon to address the emerging needs of 21st century geoscience research. The Geo-Futures program forms an alliance among geoscience professionals to help recruit, engage and retain students in the geosciences through a conference based mentoring program. The Geo-Futures program aims to 1) recruit up to forty student participants, with an emphasis on students from underrepresented groups and those with prior experience in an NSF Geoscience Research Experience for Undergraduates (REU) program; 2) engage students in innovative professional development activities; 3) provide students with high-caliber mentoring; and; 4) provide rigorous support and training for students to ensure continued interest and involvement in the geosciences. The social context of the program is the demographics of the U.S, whose composition is rapidly changing, with little reflection of this change seen in the ranks of geoscience workforce in the United States. A vigorous recruitment and outreach effort leverages connections with early career research programs from across the United States and the experience of the leaders in engaging with students from underrepresented student populations.<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.
|
07/16/2024
|
07/16/2024
|
None
|
Grant
|
47.050
|
1
|
4900
|
4900
|
2433487
|
{'FirstName': 'Corey', 'LastName': 'Garza', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Corey Garza', 'EmailAddress': '[email protected]', 'NSF_ID': '000527215', 'StartDate': '07/16/2024', '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': '178Y00', 'Text': 'GOLD-GEO Opps LeadersDiversity'}
|
2024~99933
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433487.xml'}
|
CAREER: CAS-Climate: Understanding Thermal Transport Processes in Atmospheric Boundary Layer with Utility-Scale Solar Photovoltaic Plants
|
NSF
|
01/01/2024
|
06/30/2027
| 500,493 | 283,491 |
{'Value': 'Continuing Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Sumanta Acharya', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924509'}
|
To achieve complete renewable-based electrification from the current level of less than 20% globally presents great challenges for the energy science community. This requires hundreds of trillions of kilowatt-hours of renewable energy, mainly generated through wind and solar power. One neglected but crucial question is whether extracting such huge amount of energy from the atmosphere's surface layer would alter the atmosphere's physics, leading to new climate change challenges. This CAREER project will focus on addressing whether large-scale solar photovoltaic plants alter the local climate. The research will parameterize the atmospheric response carried out by transport processes to facilitate the inclusion of solar plants in climate models. This project will pave the way for undergraduate and graduate students in middle Tennessee to become engaged in climate change education and discussion. The results of this research will enable a new "Atmospheric Transport" course at Tennessee Technological University, a textbook titled Atmospheric Transport to increase scientific literacy, and an educational mobile app ATMOSPort.<br/><br/>This project seeks to study the interactions between the near-ground atmosphere and an artificial canopy of millions of solar photovoltaic panels. A two-stage field campaign and computational fluid dynamics simulations are proposed to provide an understanding of thermal transport dynamics within the atmospheric boundary layer above thousands of acres of dark, hot, tall, and rough Photovoltaic panels of utility-scale solar plants. The knowledge gained will clarify whether such giant canopies alter the local climate and will lead to the creation of equations that accurately describe the affected atmospheric characteristics. The proposed research quantifies the significance of these impacts for various background surface conditions and parameterizes the thermal and mechanical effects of the plant to allow meteorologists and environmental engineers to incorporate them into their models efficiently. This achievement would increase the accuracy of atmospheric simulations within regions where utility-scale photovoltaic plants exist.<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
|
2433523
|
{'FirstName': 'Ahmad', 'LastName': 'Vaselbehagh', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ahmad Vaselbehagh', 'EmailAddress': '[email protected]', 'NSF_ID': '000758058', 'StartDate': '08/14/2024', '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': '140600', 'Text': 'TTP-Thermal Transport Process'}
|
2022~283491
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433523.xml'}
|
RAPID: Drivers Influencing the Persistence of Medically Adverse Cultural Practices
|
NSF
|
07/01/2024
|
06/30/2025
| 30,000 | 30,000 |
{'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': 'Jeffrey Mantz', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927783'}
|
Body modifications, sometimes accompanied with rituals, are widespread across cultures. Some of these practices have been the subject of concerted and prolonged efforts to discourage them for various reasons, including concerns for their impacts on health. However, these interventions have often been ineffective, perhaps because these practices remain fundamentally misunderstood. This project explicitly tests two competing hypotheses explaining the persistence of unhealthy body modification practices to better understand what motivates and maintains them. In doing so, the project trains an undergraduate and multiple graduate students in anthropological research methods, qualitative analysis, and quantitative modeling. Findings from this research provide a deeper understanding of body modification practices, which are disseminated in three major ways: (1) in a policy brief aimed at organizations designing interventions; (2) in meetings with participant communities; and (3) through academic presentations and publications.<br/><br/>While body modification practices are widely thought to be maintained by social norms, it is not currently clear whether the norms are reinforced by potential future marriage partners or by future peer support networks. The RAPID project takes place in a context where a potentially harmful modification practice is being decriminalized, providing an opportunity to test which social network pathway is most likely to influence its persistence. To test these two possibilities, the team utilizes focus group discussions and short surveys to assess how people share information about body modifications, what people perceive as the costs to the practices; and whether body modifications are associated with characteristics of a participants’ social support networks. The project integrates anthropological research on the social dynamics of body modification, signaling theory, and ritual, to expand the understanding of body modification and the creation of identity and cooperation more broadly.<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.
|
06/25/2024
|
06/25/2024
|
None
|
Grant
|
47.075
|
1
|
4900
|
4900
|
2433525
|
[{'FirstName': 'Laure', 'LastName': 'Spake', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Laure Spake', 'EmailAddress': '[email protected]', 'NSF_ID': '000813644', 'StartDate': '06/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Katherine', 'LastName': 'Wander', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Katherine Wander', 'EmailAddress': '[email protected]', 'NSF_ID': '000510388', 'StartDate': '06/25/2024', 'EndDate': None, 'RoleCode': 'Co-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': '139000', 'Text': 'Cultural Anthropology'}
|
2024~30000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433525.xml'}
|
ENG-QUANT: QDREAM: Quantum Dot Real-time Emulation and Autotuning Model
|
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': 'Dominique Dagenais', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922980'}
|
Silicon quantum dot devices hold significant promise for scalable quantum computing. However, tuning these devices into the desirable states for quantum applications is highly challenging, creating substantial barriers to entry. Traditionally, tuning has been a manual process that is time-consuming, heavily reliant on experimental intuition, and inherently unscalable. This situation underscores the need for automated tuning (autotuning) approaches. The development of autotuning algorithms has been impeded by the lack of experimental training data and the limitations of existing quantum dot simulators, which only capture the physics of already-tuned devices. To this end, this project aims to provide full-stack support for quantum dot device autotuning research by delivering new quantum dot device simulation infrastructures for cold start and exploring corresponding autotuning algorithms. This initiative will democratize autotuning research, offering researchers without access to experimental facilities both training data and a low-cost autotuning testbench. These advancements will promote the progress of science by facilitating broader access to quantum computing research and enhancing the efficiency and scalability of quantum dot device tuning. This project will provide training opportunities for the next-generation quantum computing workforce, and the research outcomes will be integrated into undergraduate and graduate education efforts.<br/><br/>The proposed research will significantly advance our understanding of quantum device modeling and tuning, providing innovative tools, data, and methods that can shape the tuning process of quantum dot devices. Specifically, this project will develop the QDREAM (Quantum Dot Real-Time Emulation and Autotuning Model) framework. QDREAM consists of 1) device-physics-based cold start simulations that focus on combining a finite element electrostatic simulation with a constant interaction quantum dot model to simulate devices in a completely untuned regime; 2) an FPGA-based quantum dot device emulator that will take in real voltages and output a charge sensor signal in real-time; and 3) a series of autotuning algorithms targeting various stages of the device tune-up process from cold start. QDREAM will be validated using real quadruple quantum dot devices routinely fabricated and measured in our lab. These comprehensive advancements will serve as a foundational step towards realizing larger-scale, more advanced quantum-dot-based quantum computers.<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
|
2433526
|
[{'FirstName': 'Gushu', 'LastName': 'Li', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Gushu Li', 'EmailAddress': '[email protected]', 'NSF_ID': '000932833', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Anthony', 'LastName': 'Sigillito', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Anthony J Sigillito', 'EmailAddress': '[email protected]', 'NSF_ID': '000918352', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Co-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': '191046205', 'StreetAddress': '3451 WALNUT ST STE 440A', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'PA03'}
|
{'Code': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}
|
2024~400000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433526.xml'}
|
CRII: HCC: Practical Steps Toward Integrating the Tools of Emergency Management with Crisis Informatics Techniques
|
NSF
|
12/01/2023
|
08/31/2025
| 174,987 | 3,073 |
{'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': 'Dan Cosley', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928832'}
|
This project seeks to improve how emergency managers can make use of social media posts and other information created by citizens experiencing natural disasters and other crises. This information can help document unfolding crises and reveal needs; used well, this could help emergency managers better assess crisis situations and improve their decisions about where and how to respond. However, despite recent advances in tools that use artificial intelligence techniques to analyze citizen-created information, these tools have not been effectively deployed in actual emergency response situations. This project’s goal is to make effective deployment more feasible, through analyzing the practices and training of emergency responders, identifying gaps between those practices and the technical capabilities of existing information analysis tools, and working to close the gaps through bringing emergency managers and tool developers closer together in the design process. The project team plans to work closely with emergency management organizations, a collaboration that has the potential to save lives and property, reducing suffering and the impact of crises in communities. <br/><br/>The research will proceed in two main phases. First, the project team will survey and interview emergency management practitioners about their everyday technological life. By evaluating the skills of emergency management across its respective domains (including law enforcement, fire science, homeland security, and emergency medical services), the team will provide valuable context to other researchers about where they can find stakeholders, collaborators, and space for development. The team will also collect and analyze emergency management syllabi in order to understand how emergency management students are taught to use technologies. In the second phase, the project team will conduct participatory design exercises with emergency managers that explore how tools that leverage machine learning and information retrieval could fit into their practices, using methods that simulate realistic levels of analysis accuracy in order to account for the inevitable presence of error in these tools and its effect on people’s ability to work in human-in-the-loop systems. In developing the participatory design materials, the project team will evaluate techniques like TF-IDF, Topic Modelling, Keyword-in-Context, and the underlying tools and datasets they depend on, in terms of how well they can be installed, maintained, and applied to contexts different than those they were trained on. Both phases will look at a number of contexts, allowing the research team to evaluate consistency of results across sources of information, populations, and disparate kinds of disaster events. <br/><br/>This project is jointly funded by Human Centered Computing and the Established Program to Stimulate 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.
|
05/30/2024
|
05/30/2024
|
None
|
Grant
|
47.070, 47.083
|
1
|
4900
|
4900
|
2433527
|
{'FirstName': 'Nicolas', 'LastName': 'LaLone', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nicolas J LaLone', 'EmailAddress': '[email protected]', 'NSF_ID': '000814362', 'StartDate': '05/30/2024', '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': '736700', 'Text': 'HCC-Human-Centered Computing'}
|
2021~3073
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433527.xml'}
|
Collaborative Research: Scalable Gaussian-Process Methods for Spatial Statistics and Machine Learning
|
NSF
|
08/15/2024
|
02/28/2025
| 179,936 | 185,164 |
{'Value': 'Standard Grant'}
|
{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
|
{'SignBlockName': 'Jodi Mead', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927212'}
|
The Gaussian process is a mathematical tool that can use incomplete data to fill in gaps, for example to interpolate the temperature at a person’s house given a network of nearby weather stations. Gaussian processes are used in many application areas, such as geospatial analysis, machine learning, and the analysis of computer experiments. Gaussian processes are flexible, interpretable, and provide natural quantification of uncertainty. However, direct application of Gaussian processes is too computationally expensive for large datasets. This project addresses the computational challenges with novel algorithms and bridges the gap between statistical and machine learning approaches. As big data now appear in almost every field of science and society, providing powerful, scalable, and free software to analyze such datasets can have a transformative effect. This work will replace current practices and approximations for massive spatial data that are often simplistic due to computational limitations. This project can lead to improved accuracy and uncertainty quantification in countless applications with direct impact on society, including carbon monitoring, renewable energy, rainfall prediction, calibration of robotic arms, and modeling and prediction of insurgent activities. The developed methods and software will thus be an important tool for computational and data-enabled science and engineering. The investigators will mentor and train student researchers, and share the project findings via journal publications and conference presentations.<br/><br/>The goal of this project is to develop a nearly universal toolbox for scalable Gaussian process (GP) modeling. The toolbox is based on the ordered conditional approximation (OCA), a simple but very powerful idea that exploits the screening effect (i.e., conditional independence) exhibited by many popular covariance functions. The OCA framework unifies many state-of-the-art GP approximations from statistics, machine learning, and numerical linear algebra. This project will result in new, highly accurate OCA methods with guaranteed scalability and broad applicability for modeling and analysis of nonstationary, multivariate, multi-scale, and other processes. Also, extensions will be developed that allow these new spatial-statistics methods to be used in a variety of machine-learning applications, where OCA-type approaches have not received much attention so far. For the new methods, the computational cost is guaranteed to be linear in the data size, with further speed-ups possible through parallelization. All approaches will be implemented in easy-to-use open-source software. This will allow users to bring the power of GPs to bear on modern datasets, enabling spatial prediction, calibration, parameter learning, and nonparametric regression with big data.<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
|
2433548
|
{'FirstName': 'Matthias', 'LastName': 'Katzfuss', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Matthias S Katzfuss', 'EmailAddress': '[email protected]', 'NSF_ID': '000672186', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'ZipCode': '537151218', 'PhoneNumber': '6082623822', 'StreetAddress': '21 N PARK ST STE 6301', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Wisconsin', 'StateCode': 'WI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'WI02', 'ORG_UEI_NUM': 'LCLSJAGTNZQ7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WISCONSIN SYSTEM', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'StateCode': 'WI', 'ZipCode': '537151218', 'StreetAddress': '21 N PARK ST STE 6301', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Wisconsin', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'WI02'}
|
[{'Code': '125300', 'Text': 'OFFICE OF MULTIDISCIPLINARY AC'}, {'Code': '806900', 'Text': 'CDS&E-MSS'}]
|
['2021~59686', '2022~60518', '2023~64959']
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433548.xml'}
|
Collaborative Research: RAPID: Biogeochemistry of water and sediments from a recently drained Greenland ice-marginal lake
|
NSF
|
04/01/2024
|
05/31/2024
| 64,699 | 7,154 |
{'Value': 'Standard Grant'}
|
{'Code': '06090100', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'OPP', 'LongName': 'Office of Polar Programs (OPP)'}}
|
{'SignBlockName': 'Marc Stieglitz', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924354'}
|
Water melting from glaciers flow on top of, through, and underneath glaciers, ultimately ending up in lakes or the ocean. Sometimes, this water does not take a direct path to the coast, but first enters near-shore lakes next to the glacier, called ice-marginal lakes, which can be dammed by ice. When the ice dams holding the water in these lakes fail, the water can rapidly drain to the coast over several days. The largest ice-marginal lake in Greenland is believed to be Lake Tininnilik, which recently drained into the ocean in 2021. The current low water levels mean that sediments in the lake are now exposed. This will be the first study to measure chemicals, nutrients, and microorganisms in the lake and sediments. It will also determine how lake storage changes the chemistry of water melting from the glacier. With continued climate warming, the amount of water stored in ice-marginal lakes is expected to increase, and determining the chemistry of Lake Tininnilik is important for understanding ecosystem change and carbon cycling in the coastal ocean following drainage. The project leadership includes three women, all of which are ethnic and racial minorities. As part of this project, a web-based virtual reality tour of Lake Tininnilik will be created for anyone to use. The tour will be important for other scientists trying to better understand the layout of the lake and will also be a teaching tool for the public. <br/><br/>Because of erosion and weathering under ice sheets, subglacial waters are rich in macro- and micro-nutrients. These nutrient-rich waters can be directly discharged into the ocean or stored in pro-glacial lakes, including ice-marginal lakes. Lake Tininnilik is a large ice-marginal lake restrained by an ice dam along Sarqardliup Glacier in western Greenland. It drains approximately every 10 years into a local fjord, most recently in 2021, exposing previously inundated sediments. Preliminary work prior to the 2021 drainage shows that iron (an important minor nutrient for marine phytoplankton) is 10 to 100 times greater than glacial meltwater entering the ocean directly. The iron concentrations are also paradoxically high compared to other redox sensitive element concentrations. This project will collect and analyze water samples from different lobes of Lake Tininnilik and exposed sediments to address how ice-marginal lakes change the chemical and microbial composition and availability of nutrients for near-shore and open-ocean ecosystems. Sarqardleq Fjord, into which Lake Tininnilik drains, is an important source of fish for local indigenous populations, and this work will aid future studies seeking to understand how rapid drainage events may affect the marine food web.<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
|
47.078
|
1
|
4900
|
4900
|
2433607
|
{'FirstName': 'Melisa', 'LastName': 'Diaz', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Melisa A Diaz', 'EmailAddress': '[email protected]', 'NSF_ID': '000860241', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Ohio State University', 'CityName': 'COLUMBUS', 'ZipCode': '432101016', 'PhoneNumber': '6146888735', 'StreetAddress': '1960 KENNY RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'OH03', 'ORG_UEI_NUM': 'DLWBSLWAJWR1', 'ORG_LGL_BUS_NAME': 'OHIO STATE UNIVERSITY, THE', 'ORG_PRNT_UEI_NUM': 'MN4MDDMN8529'}
|
{'Name': 'Ohio State University', 'CityName': 'COLUMBUS', 'StateCode': 'OH', 'ZipCode': '432101016', 'StreetAddress': '1960 KENNY RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Ohio', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'OH03'}
|
{'Code': '528000', 'Text': 'ANS-Arctic Natural Sciences'}
|
['2022~1634', '2023~5520']
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433607.xml'}
|
EAGER: TaskDCL: The Use of Artificial Intelligence & Synthetic Actors for Personalized Learning in Manufacturing Collaborative Robotics
|
NSF
|
09/01/2024
|
08/31/2026
| 299,953 | 299,953 |
{'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'}
|
Manufacturing is undergoing a revolutionary change, with the rise of collaborative robots, or "cobots," becoming crucial in modern factory settings. Unlike traditional industrial robots that are isolated behind safety barriers, cobots are designed to work alongside humans in the same workspace. This harmonious blend of human intelligence (Mind), physical effort (Motor), and advanced robotics (Machine) necessitates new, innovative training methods to enhance worker safety, efficiency, and satisfaction. By leveraging machine learning, AI, and spatial computing, this EArly-concept Grants for Exploratory Research (EAGER) project aims to create a personalized training framework that adapts to each worker's cognitive functions and sensorimotor skills. The goal is to improve learning outcomes and job satisfaction through adaptive instructional methods, including novel synthetic actors like avatars. If successful, this research has the potential to revolutionize workforce training, addressing skill gaps in manufacturing while promoting inclusivity and accessibility with synthetic actors that can communicate across various cultures and demographics. The implications extend beyond manufacturing, potentially benefiting sectors like healthcare and education by enhancing safety, productivity, and economic growth.<br/><br/>This research focuses on advancing personalized training strategies for complex collaborative robotic manufacturing assembly tasks. An interdisciplinary framework is employed, integrating cognitive science, manufacturing, spatial computing, human factors, artificial intelligence, and advanced robotics to create an innovative, personalized learning paradigm. This paradigm is customized to each trainee's cognitive and sensorimotor capabilities, aiming to maximize the effectiveness of training transfer. The core challenge addressed is the accurate interpretation of physiological data and its translation into real-time training modifications with the help of machine learning algorithms. This effort emphasizes the importance of understanding the complex interplay between physiological data, sensorimotor interactions, and cognitive processes. The main research questions are: How can personalized training frameworks incorporating cognitive function, sensorimotor interaction, and machine learning improve the efficiency and effectiveness of workers in collaborative robotic manufacturing environments? What are the impacts of integrating synthetic actors and wearable physiological monitoring on cognitive workload and task performance in learning transfer for complex manufacturing tasks? How does real-time adaptive instruction driven by AI and biometric feedback influence human workers' safety, efficiency, and satisfaction in collaborative robotic training settings? The insights gained are expected to enhance training methodologies, ultimately fostering a more capable and adaptable workforce equipped to navigate the future of complex manufacturing environments.<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
|
2433608
|
[{'FirstName': 'Laura', 'LastName': 'Stanley', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Laura M Stanley', 'EmailAddress': '[email protected]', 'NSF_ID': '000555244', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Apostolos', 'LastName': 'Kalatzis', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Apostolos Kalatzis', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A01CG', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Montana State University', 'CityName': 'BOZEMAN', 'ZipCode': '59717', 'PhoneNumber': '4069942381', 'StreetAddress': '216 MONTANA HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Montana', 'StateCode': 'MT', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'MT01', 'ORG_UEI_NUM': 'EJ3UF7TK8RT5', 'ORG_LGL_BUS_NAME': 'MONTANA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Montana State University', 'CityName': 'BOZEMAN', 'StateCode': 'MT', 'ZipCode': '59717', 'StreetAddress': '216 MONTANA HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Montana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'MT01'}
|
[{'Code': '058Y00', 'Text': 'M3X - Mind, Machine, and Motor'}, {'Code': '164200', 'Text': 'Special Initiatives'}]
|
2024~299953
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433608.xml'}
|
CAREER: Understanding the Stabilizing Role of Muscle-Tendon Units in vivo
|
NSF
|
10/01/2023
|
09/30/2026
| 785,011 | 135,991 |
{'Value': 'Continuing Grant'}
|
{'Code': '08090000', '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'}
|
This CAREER project combines research, training, and educational activities that focus on advancing knowledge of how muscles and tendons function during standing and walking. It is well understood that muscles in the lower body produce forces and that tendons, which attach to muscles, transmit those forces to the skeleton, allowing animals to stand and walk. However, most current knowledge about muscle and tendon comes from experiments that study these tissues when functioning outside of the body. What is not well understood is how muscle and tendon function as an integrated system within the body and, in particular, how they function to meet the demands of maintaining balance while moving. This project will measure the mechanical behavior of muscle and tendon when the body responds to a push intended to challenge the ability to maintain balance. Integrated within the research component is training for two students from underrepresented groups pursuing a PhD in STEM. These students will gain knowledge in the field, develop first-hand experience in carrying out scientific experiments, and develop as leaders in the next generation of interdisciplinary scientists. This CAREER project will impact society by translating new knowledge about how muscle and tendon function during movement by (1) contributing design principles for biologically inspired prosthetics and (2) developing teaching units and workshops offered to students at the Multicultural Education and Counseling through the Arts (MECA) non-profit organization, which serves K-12 grade students (~4,000 underserved youth) in Houston’s historic 6th Ward.<br/><br/>This CAREER project focuses on understanding the role of muscle-tendon units to control movement and stability using a live, freely moving animal, and integrates research, education, training, and outreach. Movement stabilization can be accomplished by several interacting mechanisms: a muscle’s force-modulating properties, the energy-modulating capacity of variable-stiffness tendon springs, and the co-behavior of agonist-antagonist muscle-tendon units. The project’s primary research objectives and outcomes are to use a work-energy based framework to: (1) Determine the muscle-tendon unit properties that modulate the rapid flow of energy absorption during active lengthening in situ. (2) Determine the properties that allow ankle joint agonist-antagonist muscle-tendon units to govern the response of destabilizing perturbations elicited during standing in vivo. (3) Determine the properties that allow ankle joint agonist-antagonist muscle-tendon units to govern the response of destabilizing perturbations elicited during walking in vivo. The experimental approach involves the use of a custom-built, high performance linear actuator to elicit unexpected perturbations to the body during standing and walking. Custom sensors implanted into muscle-tendon tissue and force platform measurements are used to understand the response to perturbations at multiple scales, from muscle-tendon units that control ankle joint function to whole body mechanics. In addition, the project will implement an educational outreach plan that will advance a summer STEM camp curriculum that serves K-12th graders from underrepresented groups. The hands-on activities to be developed will focus on key biomechanical concepts that integrate math, physics, and physical 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.
|
05/31/2024
|
05/31/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2433611
|
{'FirstName': 'Christopher', 'LastName': 'Arellano', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christopher J Arellano', 'EmailAddress': '[email protected]', 'NSF_ID': '000781910', 'StartDate': '05/31/2024', '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': '857245064', 'StreetAddress': 'PO Box 245064', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Arizona', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'AZ07'}
|
{'Code': '765800', 'Text': 'Physiol Mechs & Biomechanics'}
|
['2022~7312', '2023~128679']
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433611.xml'}
|
I-Corps: Translation Potential of a Point-of-Care Drug Detection System
|
NSF
|
09/01/2024
|
02/28/2025
| 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': 'Molly Wasko', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924749'}
|
The broader impact of this I-Corps project is based on the development of new diagnostic and detection technology that is a simple and easy to use point-of-care drug test to aid in overdose prevention and treatment. This innovative testing solution has the potential to provide rapid results, allow immediate clinical action, and reduce emergency department stays. Rapid and accurate drug screening is crucial for patient management and treatment decisions, especially in emergency settings, pain management centers, and maternal fetal medicine clinics. By reducing diagnostic time, this technology can improve patient outcomes and reduce costs for patients, hospitals, and insurance companies.<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. The solution is based on the development of methods to design and characterize protein-based sensors for small molecules. Candidate sensors are screened in a high-throughput cell-based assay which couples the chemically sensitive binding of protein and deoxyribonucleic acid (DNA) to gene expression. Using methods in high throughput sequencing, the sensitivity of proteins to different molecules is measured using relative gene expression as a proxy. These protein-based sensors could be formatted as paper-based drug panels, yielding the benefits of reduced assay complexity and higher information density for diagnosing patient conditions, such as the presence of drugs of abuse in clinical settings.<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
|
2433640
|
{'FirstName': 'Srivatsan', 'LastName': 'Raman', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Srivatsan Raman', 'EmailAddress': '[email protected]', 'NSF_ID': '000747423', 'StartDate': '07/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'ZipCode': '537151218', 'PhoneNumber': '6082623822', 'StreetAddress': '21 N PARK ST STE 6301', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Wisconsin', 'StateCode': 'WI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'WI02', 'ORG_UEI_NUM': 'LCLSJAGTNZQ7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WISCONSIN SYSTEM', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'StateCode': 'WI', 'ZipCode': '537151218', 'StreetAddress': '21 N PARK ST STE 6301', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Wisconsin', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'WI02'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433640.xml'}
|
Expanding Access through Educational Instrumentation: Enhancing STEM Undergraduate Education
|
NSF
|
10/01/2024
|
09/30/2026
| 179,873 | 179,873 |
{'Value': 'Standard Grant'}
|
{'Code': '11040100', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DUE', 'LongName': 'Division Of Undergraduate Education'}}
|
{'SignBlockName': 'Mike Ferrara', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922635'}
|
With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI Program), this Educational Instrumentation project at Los Angeles Mission College (LAMC) will strengthen undergraduate learning in chemistry, physics, engineering, and computer science. Specifically, this project will secure a nuclear magnetic resonance spectrometer, gas chromatograph, electron diffraction equipment, a 3D land surveying scanner, Arduino and Raspberry PI kits, and a selection of other equipment to support students in surveying, robotics, and engineering courses. These equipment will enrich 17 courses serving over 1500 students per year and will allow students to participate in authentic, hands-on training relevant to the STEM workforce. In addition to providing improved experiences for undergraduates pursuing STEM degrees at LAMC across multiple courses, the new equipment will also be used to offer summer bootcamps for Los Angeles high school students that will highlight authentic STEM skills and career opportunities. <br/><br/>The goals of this project are to enrich the learning and experiences of undergraduate students by providing critical equipment in chemistry, physics, engineering, and computer science. Across multiple lab and field courses at LAMC, students will utilize the new equipment to build skills and explore topics that would be relatively inaccessible without modern technology. The project will assess the impact of the project-funded equipment using institutional data and post-course surveys. This project is funded by the HSI Program, which aims to enhance undergraduate STEM education, broaden participation in STEM, and increase capacity to engage in the development and implementation of innovations to improve STEM learning and teaching at HSIs.<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
|
2433665
|
{'FirstName': 'Parvaneh', 'LastName': 'Mohammadian', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Parvaneh Mohammadian', 'EmailAddress': '[email protected]', 'NSF_ID': '000626444', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Los Angeles Mission College', 'CityName': 'SYLMAR', 'ZipCode': '913423200', 'PhoneNumber': '8183647600', 'StreetAddress': '13356 ELDRIDGE AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '29', 'CONGRESS_DISTRICT_ORG': 'CA29', 'ORG_UEI_NUM': 'C54LC7CTL7M5', 'ORG_LGL_BUS_NAME': 'LOS ANGELES COMMUNITY COLLEGE DIST', 'ORG_PRNT_UEI_NUM': 'Y9SWL6BWDM85'}
|
{'Name': 'Los Angeles Mission College', 'CityName': 'SYLMAR', 'StateCode': 'CA', 'ZipCode': '913423200', 'StreetAddress': '13356 ELDRIDGE AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '29', 'CONGRESS_DISTRICT_PERF': 'CA29'}
|
{'Code': '077Y00', 'Text': 'HSI-Hispanic Serving Instituti'}
|
2024~179873
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433665.xml'}
|
Conference: NSF-JST Workshop on Secure and Resilient Smart Living CPS
|
NSF
|
07/01/2024
|
06/30/2025
| 24,999 | 24,999 |
{'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 envisioned era of “smart living” aims to improve human quality of life and experience, leading to a better and safer society, with the help of smart sensors and devices, the Internet of Things (IoT), and cyber-physical systems (CPS) coupled with advanced data analytics, artificial intelligence (AI) and machine learning (ML) techniques. The voluminous data collected from smart living applications (e.g., smart buildings/cities, smart energy, smart transportation, smart manufacturing, smart health, smart agriculture, disaster response) are vulnerable to a wide variety of security threats and privacy/trust breaches, thwarting the accuracy of decision making and operational impacts on which the modern society depends. Attack (or anomaly) detection in smart living CPS poses unique challenges since the collected data are also affected by the behavioral randomness of human users. Privacy and trust issues in smart societies are exacerbated owing to socio-economic-cultural differences. In addition, one needs to consider the tradeoff between privacy, safety, and security which are important at a practical level to the community members.<br/><br/>Recognizing the research challenges and opportunities in smart and connected communities, in recent years the NSF and the Japan Science and Technology (JST) Agency have established joint funding programs to support collaborative cutting-edge research and development in smart living. This proposal aims to continue and advance that dialog, by requesting funds for US researchers to participate in the NSF-JST Workshop on Secure and Resilient Smart Living CPS to be held in Osaka, Japan on July 2-3, 2024. The outcome of the workshop will be to catalyze mutually beneficial areas of further collaborations between the researchers in the US and Japan in the areas of security, privacy, trust, resilience, safety, dependability, and robustness of smart living CPS, potentially leading to joint funding opportunities. Such bilateral cooperation will help establish stronger US-Japan strategic alliance in research, education, technology innovation, entrepreneurship, and workforce development that can benefit the citizens and society at large in both countries.<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
|
47.070
|
1
|
4900
|
4900
|
2433666
|
{'FirstName': 'Sajal', 'LastName': 'Das', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sajal K Das', 'EmailAddress': '[email protected]', 'NSF_ID': '000430507', 'StartDate': '07/11/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Missouri University of Science and Technology', 'CityName': 'ROLLA', 'ZipCode': '654091330', 'PhoneNumber': '5733414134', 'StreetAddress': '300 W. 12TH STREET', 'StreetAddress2': '202 CENTENNIAL HALL', 'CountryName': 'United States', 'StateName': 'Missouri', 'StateCode': 'MO', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_ORG': 'MO08', 'ORG_UEI_NUM': 'Y6MGH342N169', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MISSOURI SYSTEM', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Missouri University of Science and Technology', 'CityName': 'ROLLA', 'StateCode': 'MO', 'ZipCode': '654091330', 'StreetAddress': '300 W. 12TH STREET', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Missouri', 'CountryFlag': '1', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_PERF': 'MO08'}
|
{'Code': '033Y00', 'Text': 'S&CC: Smart & Connected Commun'}
|
2024~24999
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433666.xml'}
|
RAPID: Instrumentation, Calibration, and Field Work Planning for an Expedition to Antarctica's Lowest Temperature Site
|
NSF
|
08/15/2024
|
07/31/2025
| 38,912 | 38,912 |
{'Value': 'Standard Grant'}
|
{'Code': '06090300', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'OPP', 'LongName': 'Office of Polar Programs (OPP)'}}
|
{'SignBlockName': 'Kelly Brunt', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928457'}
|
Satellite measurements of the surface snow temperatures on the East Antarctic Plateau have identified an extensive area where mid-winter conditions are frequently below -90°C. A specialized surface observation station has been built and partially tested and is intended to link surface observations with the satellite data. The station is designed to measure surface conditions, including wind and blowing snow. These data will be transmitted during the Antarctic winter. The site will also be instrumented with two cold-rated automated weather stations (AWS). This RAPID award would specifically support the further development and calibration of the existing instrument suite, add an additional sensor (to measure wind and blowing snow), and test the station under realistic field conditions. The project would leverage the logistics of another Antarctic national program and outside, private providers to deploy these sensors. Ultimately, the dataset could lead to public interest, which could in turn provide opportunity to publicly discuss polar climate change.<br/><br/>The goal of this RAPID is to establish the coldest temperature that can be reached on Earth’s surface to better understand the weather and climate controls on the lowest-temperature events. The site on the East Antarctic Plateau of the most frequent occurrence of <-98°C conditions is located ~100 km from the Pole of Inaccessibility. At roughly 100 smaller valley sites within this region (typically ~5 square km in area), surface snow temperatures can reach -98°C. Air temperatures at these sites at 2 m height are likely a few degrees above this value due to the intense near-surface gradients that form under clear-sky conditions during polar night, and are estimated to be -94 ± 2°C. The recognized lowest surface air temperature record is -89.2°C, measured at Vostok Station in July 1983.<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
|
47.078
|
1
|
4900
|
4900
|
2433668
|
{'FirstName': 'Ted', 'LastName': 'Scambos', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ted A Scambos', 'EmailAddress': '[email protected]', 'NSF_ID': '000240405', 'StartDate': '08/09/2024', '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': '511600', 'Text': 'ANT Glaciology'}
|
2024~38912
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433668.xml'}
|
RUI: Effects of Traffic Noise on Avian Cognition
|
NSF
|
02/01/2024
|
06/30/2025
| 350,000 | 302,668 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Jodie Jawor', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927887'}
|
Human-derived noise pollution is a ubiquitous feature of many landscapes and has been shown to have a variety of negative effects on the ecology and behavior of animals. Recent research indicates that noise pollution could also affect how well animals learn to solve problems. This award examines the mechanism through which noise pollution affects animal cognition and will help determine whether animals living in noisy habitats (e.g., near highways or busy cities) can overcome the negative impacts of these noise sources on their cognitive performance. This research will provide generalizable insights about how animals respond to changing environmental conditions and will have key implications for the conservation of animal populations. With similar negative effects of noise on cognitive function also proposed for humans, better understanding this relationship will also likely have direct application to the welfare of human societies. The award will provide key infrastructure and research capability at a primarily undergraduate and minority-serving institution, leading directly to numerous opportunities for undergraduate students to gain hands-on research experiences that will help support their future careers in science, especially from groups who have traditionally been underrepresented in STEM fields. <br/><br/><br/>Anthropogenic noise has a number of detrimental impacts on animal physiology, behavior, populations, and communities. A recent study demonstrated further negative effects on cognitive function in one species of captive-raised songbird, but this phenomenon has been little studied and the mechanisms driving this relationship are unknown. The goal of this research is to determine whether traffic noise similarly impacts cognition in other songbird species and whether animals that regularly encounter noise pollution in their environment continue to experience the same level of reduced cognitive performance as naïve individuals. This research will expose birds to foraging tasks designed to measure a variety of aspects of animal cognition (e.g., inhibitory control, motor learning, associative learning, spatial memory, etc.) under varying road traffic noise regimes. This research will make several advances by examining how varying the type and duration of traffic noise exposure impacts cognitive performance in birds held under carefully controlled laboratory conditions, determining whether previous findings extend to wild songbird species, and establish whether noise differentially affects those animals living in wild populations that are more exposed to noise pollution. The results of this award will shed light on the mechanisms driving noise-induced cognitive inhibition, with implications for cognitive science, animal behavior, urban ecology, and conservation.<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.
|
05/22/2024
|
05/22/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2433677
|
{'FirstName': 'Christopher', 'LastName': 'Templeton', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christopher Templeton', 'EmailAddress': '[email protected]', 'NSF_ID': '000716692', 'StartDate': '05/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Western Washington University', 'CityName': 'BELLINGHAM', 'ZipCode': '982255996', 'PhoneNumber': '3606502884', 'StreetAddress': '516 HIGH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Washington', 'StateCode': 'WA', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'WA02', 'ORG_UEI_NUM': 'U3ZFA57417D4', 'ORG_LGL_BUS_NAME': 'WESTERN WASHINGTON UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'U3ZFA57417D4'}
|
{'Name': 'Western Washington University', 'CityName': 'BELLINGHAM', 'StateCode': 'WA', 'ZipCode': '982255996', 'StreetAddress': '516 HIGH ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Washington', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'WA02'}
|
{'Code': '765900', 'Text': 'Animal Behavior'}
|
2022~302668
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433677.xml'}
|
Travel: NSF Student Travel Grant for 2024 International Conference on Distributed Computing Systems (ICDCS 2024)
|
NSF
|
07/15/2024
|
06/30/2025
| 10,000 | 10,000 |
{'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': 'Danella Zhao', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924434'}
|
The purpose of this travel grant is to broaden and diversify the student participation in the 44th International Conference on Distributed Computing Systems (ICDCS 2024), sponsored by the Institute of Electrical and Electronics Engineers (IEEE), a premier annual international forum for the presentation of research results in distributed computing. It seeks to increase student participation in the conference and the field. The requested funding would support the travel of eligible students from US universities and institutions to the conference. <br/><br/>This travel grant encourages the involvement of students in the field who are not well funded and those who are just beginning their participation in the field or are interested in entering it. A special effort is made to reach out to women, people from underrepresented populations in computing, students from Minority-Serving Institutions, and students from institutions in jurisdictions eligible to NSF’s Established Program to Stimulate Competitive Research (EPSCoR). Preference is also given to students who will present their research at ICDCS.<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.
|
07/12/2024
|
07/12/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2433680
|
{'FirstName': 'Xiaodong', 'LastName': 'Zhang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xiaodong Zhang', 'EmailAddress': '[email protected]', 'NSF_ID': '000416471', 'StartDate': '07/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Ohio State University', 'CityName': 'COLUMBUS', 'ZipCode': '432101016', 'PhoneNumber': '6146888735', 'StreetAddress': '1960 KENNY RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'OH03', 'ORG_UEI_NUM': 'DLWBSLWAJWR1', 'ORG_LGL_BUS_NAME': 'OHIO STATE UNIVERSITY, THE', 'ORG_PRNT_UEI_NUM': 'MN4MDDMN8529'}
|
{'Name': 'Ohio State University', 'CityName': 'COLUMBUS', 'StateCode': 'OH', 'ZipCode': '432101016', 'StreetAddress': '1960 KENNY RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Ohio', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'OH03'}
|
{'Code': '779800', 'Text': 'Software & Hardware Foundation'}
|
2024~10000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433680.xml'}
|
Support for Broadening Participation in the 28th AACG Western Section Conference on Crystal Growth & Epitaxy; Fallen Leaf Lake, California; 9-12 June 2024
|
NSF
|
06/01/2024
|
11/30/2024
| 17,250 | 17,250 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Tom Kuech', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922218'}
|
The design and synthesis of new materials and processes for growth of crystals is important for technological advances. The biennial American Association for Crystal Growth Conference (West) brings together researchers in diverse areas spanning natural sciences and engineering to present their latest findings. The secluded setting of the conference offers a unique platform for exchange of ideas in fundamental and applied areas related to crystal growth. Recent trends in the crystal growth community have revealed challenges in translating crystal growth technologies to industrial manufacturing processes, and in training a diverse workforce for sustaining the innovation economy. To this end, the organizing committee for the 28th version of the conference has included an advanced manufacturing component within the conference program. The award will support the attendance of early-stage researchers and students at the conference (graduate, undergraduate and high school) with emphasis on students from underrepresented communities from universities and high schools all over the country. The award will also support the organization of a panel discussion on student career planning and guidance. The initiatives in this and future versions of the conference to help several manufacturing technologies through development of interdisciplinary projects and collaborations, and for the education and training of a new generation of diverse workforce within the crystal growth community. <br/><br/>The organizing committee for the conference has selected topics in areas of biomimetics, biocrystallization, energy materials, environmental systems, functional materials, and fundamental aspects of crystallization. With participation from industry, academia, and national laboratories, the conference allows a unique set of collaborations that underscore the issues and solutions in fundamental and application-focused aspects of crystal growth. Within each topic, there is an emphasis on addressing challenges in scaling up the synthesis techniques to industry-scale manufacturing platforms with data-enabled AI and machine-learning based techniques. These interdisciplinary bridges are needed to realize the transformative potential for several crystal growth principles and technologies in understanding, engineering, and manufacturing of crystals. The manufacturing focus in this meeting should serve as a template for future meetings to strengthen the nexus between manufacturing and crystal growth. Recruitment efforts are aimed at building a conference program that encouraged participation of several speakers new to the crystal growth community and to the AACG society, including early-stage researchers and students from underrepresented communities. The conference program and abstracts will be disseminated through the AACG website and through AACG newsletter.<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.
|
06/24/2024
|
06/24/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2433683
|
{'FirstName': 'Moneesh', 'LastName': 'Upmanyu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Moneesh Upmanyu', 'EmailAddress': '[email protected]', 'NSF_ID': '000321484', 'StartDate': '06/24/2024', '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': '088Y00', 'Text': 'AM-Advanced Manufacturing'}
|
2024~17250
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433683.xml'}
|
I-Corps: Translation potential of a mobile unit for disaster recovery personnel
|
NSF
|
06/15/2024
|
11/30/2024
| 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': 'Ruth Shuman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922160'}
|
The broader impact of this I-Corps project is the development of a portable, mobile shelter for disaster recovery personnel and survivors in disaster areas. When a disaster strikes a rural or other community, whether it’s a tornado, wildfire, or flooding, the effects are compounded by the lack of available housing for survivors and recovery personnel. Access becomes difficult with hotel and hospital bed space in short supply and geographically dispersed supplies. This disaster mobile unit is designed to be self-sufficient and self-sustaining with solar power, air conditioning, water filtration for drinking water, and secure doors for safety. In addition, the unit includes a communications package to support effective government communication and networking and a medical configuration that could provide an area for medical personnel to treat patients closer to the disaster. <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 energy-sustainable mobile shelters for disaster survivors and recovery personnel. The shelters are designed to provide living quarters, medical access, and communications equipment in times of emergency. The disaster mobile unit is constructed with insulation technologies that minimize its carbon footprint and is paired with high-efficiency solar power generation and water filtration systems to create a shelter that may be deployed into remote areas and set up with minimal infrastructure requirements. The self-sustaining units may provide comfortable conditions when fuel and supporting infrastructure are absent due to post-disaster conditions. the technology allows communities to recover more quickly and also provides continuity of local government and community function during a disaster or immediately after a storm.<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.
|
06/04/2024
|
06/04/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2433700
|
{'FirstName': 'James', 'LastName': 'Williams', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': 'Jr', 'PI_FULL_NAME': 'James R Williams', 'EmailAddress': '[email protected]', 'NSF_ID': '000993338', 'StartDate': '06/04/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Louisiana at Lafayette', 'CityName': 'LAFAYETTE', 'ZipCode': '705032014', 'PhoneNumber': '3374825811', 'StreetAddress': '104 E UNIVERSITY AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Louisiana', 'StateCode': 'LA', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'LA03', 'ORG_UEI_NUM': 'C169K7T4QZ96', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF LOUISIANA AT LAFAYETTE', 'ORG_PRNT_UEI_NUM': 'C169K7T4QZ96'}
|
{'Name': 'University of Louisiana at Lafayette', 'CityName': 'LAFAYETTE', 'StateCode': 'LA', 'ZipCode': '705032014', 'StreetAddress': '104 E UNIVERSITY CIR 3RD FL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Louisiana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'LA03'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433700.xml'}
|
I-Corps: Translation potential of a compostable, pressure-sensitive adhesive
|
NSF
|
07/01/2024
|
12/31/2024
| 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': 'Ruth Shuman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922160'}
|
The broader impact of this I-Corps project is the development of a pressure sensitive adhesive to be used in labeling, packaging, and tapes that may be home composted. Currently, adhesives are nondegradable products. There are no commercially viable, home-compostable, pressure-sensitive adhesives. The developing composting infrastructure in the United States must accept compostable food packaging to divert food waste and emissions from landfills. Contamination of non-degradable plastic labels in the compost poses a risk to the growth of the composting infrastructure. This adhesive is designed to replace current nondegradable labels and is a drop-in replacement in many applications. This solution may reduce landfilling of post-consumer plastic waste, helping to address the growing plastic pollution problem. In addition, this adhesive will be the first home-compostable, pressure-sensitive adhesive meeting the current market need for sustainable adhesives to pair with other biodegradable materials.<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 a home compostable pressure-sensitive adhesive. Pressure-sensitive adhesives are widely used to easily fasten two materials together in either a permanent or non-permanent bond. Currently, all commercially available pressure-sensitive adhesives are nondegradable, and most will be sent to a landfill at the end of their useful life. This adhesive was developed based upon a market need for sustainable adhesives to pair with other current and emerging sustainable materials. The adhesive material biodegrades via microorganisms at 21°C, allowing the material to be home composted. In addition, the organic carbon of the material is mineralized greater than 90% within four months of testing, which is eight months faster than the one year permitted for certification testing. The mechanical properties of the adhesives are tunable to meet a wide range of application demands in line with current commercial adhesives and can be either removable or permanent. The adhesive has been produced in pilot reactors, applied successfully on an industrial coating line, and successfully converted into labels using conventional die-cutting and processing equipment. With a current 72% biobased carbon content, the adhesive further reduces the reliance on petroleum feedstocks. The technoeconomic analysis completed for the material shows commercial viability as a sustainable product.<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.
|
07/01/2024
|
07/01/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2433711
|
[{'FirstName': 'Evan', 'LastName': 'White', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Evan M White', 'EmailAddress': '[email protected]', 'NSF_ID': '000845870', 'StartDate': '07/01/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jason', 'LastName': 'Locklin', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jason Locklin', 'EmailAddress': '[email protected]', 'NSF_ID': '000075874', 'StartDate': '07/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Dan', 'LastName': 'Geller', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dan Geller', 'EmailAddress': '[email protected]', 'NSF_ID': '000667896', 'StartDate': '07/01/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Georgia', 'CityName': 'ATHENS', 'ZipCode': '306020001', 'PhoneNumber': '7065425939', 'StreetAddress': '623 BOYD GRADUATE RESEARCH CTR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'GA10', 'ORG_UEI_NUM': 'Q2LKTLYJM4P8', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF GEORGIA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Georgia', 'CityName': 'ATHENS', 'StateCode': 'GA', 'ZipCode': '306020001', 'StreetAddress': '623 BOYD GRADUATE RESEARCH CTR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'GA10'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433711.xml'}
|
CDS&E: Collaborative Research: Development and Application of Machine Learning Classification of Optical Transients
|
NSF
|
06/01/2024
|
08/31/2025
| 398,737 | 207,876 |
{'Value': 'Standard Grant'}
|
{'Code': '03020000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'AST', 'LongName': 'Division Of Astronomical Sciences'}}
|
{'SignBlockName': 'Nigel Sharp', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924905'}
|
This project will develop, test, and use, a range of machine learning (ML) algorithms and pipelines for the photometric classification of optical transients from current and future surveys. The discovery rate of optical transients already outpaces traditional spectroscopic classification methods, and with future surveys only a tiny fraction of their discoveries can be observed spectroscopically. Photometric classification is therefore essential, for identifying rare transients in real time, for classifying transients to allow population studies, and for discovering new classes of transient. Each of these goals requires different ML and algorithmic approaches. Now that appropriate data are in hand and usable for initial classification tests, this is the right time to test the pipelines to be used for the real-time discovery of rare transients, in preparation for future much larger data volumes. Students and postdocs will gain experience developing and implementing ML algorithms, carrying out spectroscopic and multi-wavelength studies of astronomical transients. This experience will feed into undergraduate education, connecting classroom learning and hands-on research and involving non-computer science majors, including student observing with large-aperture telescopes, and science fair experiences for K-12 students.<br/><br/>This project builds on recent successes by this team in creating initial classification pipelines using a range of ML algorithms, which were trained on, and then applied to, real data. It draws on a combination of large survey data, ML techniques, and active multi-wavelength follow-up, to prepare students and postdocs for Big Data scientific techniques in astronomy. This project will develop pipelines to: (i) combine time-series based light curve classification with image-based host galaxy classification; (ii) develop, test, and implement ML pipelines targeted at specific classes of known rare transients; and (iii) design algorithms for anomaly detection to discover new types of rare transients. The classification tools produced by this work will be used for a wide range of time-domain astrophysics applications.<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
|
2433718
|
{'FirstName': 'Victoria', 'LastName': 'Villar', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Victoria A Villar', 'EmailAddress': '[email protected]', 'NSF_ID': '000809398', 'StartDate': '05/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Harvard University', 'CityName': 'CAMBRIDGE', 'ZipCode': '021385366', 'PhoneNumber': '6174955501', 'StreetAddress': '1033 MASSACHUSETTS AVE STE 3', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MA05', 'ORG_UEI_NUM': 'LN53LCFJFL45', 'ORG_LGL_BUS_NAME': 'PRESIDENT AND FELLOWS OF HARVARD COLLEGE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Harvard University', 'CityName': 'CAMBRIDGE', 'StateCode': 'MA', 'ZipCode': '021385366', 'StreetAddress': '1033 MASSACHUSETTS AVE STE 3', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'MA05'}
|
{'Code': '121700', 'Text': 'EXTRAGALACTIC ASTRON & COSMOLO'}
|
2021~207876
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433718.xml'}
|
EAGER: Investigate the structural and electronic properties of Pd1-N8/CNT
|
NSF
|
07/01/2024
|
08/31/2025
| 150,000 | 166,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Robert McCabe', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924826'}
|
Selective hydrogenation of acetylene to ethylene is an important industrial purification process that removes trace amount of acetylene from ethylene, thus protecting downstream chemical processes that convert ethylene to polymers and other important chemicals. This EArly-concept Grant for Exploratory Research (EAGER) project will investigate the structural and electronic properties of a novel catalyst design for selective acetylene conversion to ethylene. The catalyst design has already shown improved performance with respect to conventional catalyst designs. However, additional research is needed to better understand the mechanisms by which the catalyst works, thus opening the door to improved performance and extension of the catalyst design to additional materials combinations and other reactions. The project also provides resources for the investigator to train undergraduate and high-school students in aspects of catalysis research.<br/><br/>The project focuses on improved design of a novel catalyst structure consisting of metal (M) single-atoms catalysts (M-SACs) supported on carbon nanotubes (CNTs). In particular, the design consists of Pd single-atoms deposited on 8-member polynitrogen strands anchored on the CNTs (i.e., Pd1-N8/CNT). The catalyst design provides a high density of active sites for hydrogen splitting, consisting of proximate N and Pd single sites that work in concert to both adsorb acetylene and react it with H-atoms to ethylene. Although the investigator’s preliminary work confirms that a Pd1-N8/CNT catalyst system is significantly more selective than CNTs without the polynitrogen structure, additional details regarding the differences in properties are needed to advance the concept. Thus, the project will employ a suite of characterization methods including HR-TEM, XPS, XAFS, TPD and CO-DRIFTs techniques, to probe the structural and electronic properties of the Pd1-N8/CNT catalyst versus the baseline (i.e. non-SAC) Pd-N/CNT catalyst. The resulting data will open the door to optimization studies and extension of the design to additional materials and hydrogenation reactions.<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
|
08/01/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2433721
|
{'FirstName': 'Xianqin', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xianqin Wang', 'EmailAddress': '[email protected]', 'NSF_ID': '000524525', 'StartDate': '07/10/2024', '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': '140100', 'Text': 'Catalysis'}
|
2024~166000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433721.xml'}
|
EAGER: The Biothreats Emergence, Analysis, and Communications Network (BEACON)
|
NSF
|
07/01/2024
|
06/30/2025
| 199,979 | 199,979 |
{'Value': 'Standard Grant'}
|
{'Code': '08010000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'DEB', 'LongName': 'Division Of Environmental Biology'}}
|
{'SignBlockName': 'Samuel Scheiner', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927175'}
|
This project will develop an open-source Large Language Model that will be able to identify, verify, prioritize, summarize and predict outcomes of disease emergence events in humans, other animals, and plants. That model will link detected signals and model outputs to human verification and public health context with the goal of sharing event reports on a publicly available web platform. BEACON, based at Boston University’s Center on Emerging infectious Diseases, is a web-based platform and accompanying public health program which aims to address this need by leveraging advanced AI and a global network of human subject matter experts to rapidly collect, analyze, and disseminate information on emerging disease threats. The current lack of similar free resources for the global community makes this initiative both<br/>transformative and timely. The impact of an independent, open-access, disease surveillance platform that utilizes advanced AI with human subject-matter oversight for near real-time reporting and analysis of emerging threats is substantial. BEACON will aid in global capacity strengthening and tailored international and national preparedness and response. It will empower policymakers, public health, and healthcare practitioners, and the public through actionable information, ultimately driving proactive measures to prevent and mitigate the spread of emerging threats.<br/><br/>The exploratory approach of integrating AI/LLM into both discovery and assessment of new biological events will create a specialized large language model for processing vast datasets in order to detect potential biothreats. The developing machine learning algorithms will be capable of predicting the epidemic and pandemic potential of any new outbreak by integrating AI findings and predictive intelligence with trusted human expert verification and analysis. The LLM will be used to classify and rank new signals and reports depending on their relevance and importance, provide features (text embeddings) for predictive modeling, and compose/translate reports to be edited/approved by human subject matter experts. It will produce reports and data tools that will provide context for action, and disseminate and share the data and analyses via a user-friendly multilingual web platform that will operate as a global public good.<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.
|
07/23/2024
|
07/23/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2433726
|
[{'FirstName': 'Ioannis', 'LastName': 'Paschalidis', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ioannis Paschalidis', 'EmailAddress': '[email protected]', 'NSF_ID': '000104809', 'StartDate': '07/23/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'John', 'LastName': 'Brownstein', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'John Brownstein', 'EmailAddress': '[email protected]', 'NSF_ID': '000621063', 'StartDate': '07/23/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Nahid', 'LastName': 'Bhadelia', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nahid Bhadelia', 'EmailAddress': '[email protected]', 'NSF_ID': '000864664', 'StartDate': '07/23/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Trustees of Boston University', 'CityName': 'BOSTON', 'ZipCode': '022151703', 'PhoneNumber': '6173534365', 'StreetAddress': '1 SILBER WAY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'THL6A6JLE1S7', 'ORG_LGL_BUS_NAME': 'TRUSTEES OF BOSTON UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Trustees of Boston University', 'CityName': 'BOSTON', 'StateCode': 'MA', 'ZipCode': '022151703', 'StreetAddress': '1 SILBER WAY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}
|
{'Code': 'Y10400', 'Text': None}
|
2024~199979
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433726.xml'}
|
I-Corps: Translation Potential of a Microsensor Systems for Monitoring Fuel Cell Membrane Degradations for Electric Vehicles
|
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 microsensors for real-time monitoring of fuel cell membrane degradation in electric vehicles. This diagnostic tool will provide researchers with valuable insights into degradation mechanisms, allowing for targeted improvements in performance and durability. By increasing the efficiency and reliability of hydrogen fuel cells, this technology will contribute to environmental sustainability. The technology also holds the promise of economic benefits by reducing reliance on limited natural resources. By exploring various market segments and conducting extensive and intensive customer discovery, starting with fuel cell electrical vehicle companies, the project will enhance the understanding of existing methods and customer challenges. The potential commercial impact on the transportation industry and companies focused on sustainable clean energy development using hydrogen fuel cell power systems will be thoroughly examined. This comprehensive approach will help identify new opportunities and refine the technology to effectively meet market demands.<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 ion-sensitive microsensors, chosen for their affordability, compactness, durability, and suitability for continuous real-time monitoring of fuel cell membrane degradation. In low-temperature proton exchange membrane fuel cells, radical attacks cause polymer chain breaks and irreversible reactions, leading to thinning of the ionomer and the release of fluorinated and other degradation materials into the reactant outlet streams. These attacks compromise the performance and stability of the membrane electrode assembly. To combat this, the technology employs highly fluoride-sensitive membranes for microsensors, integrating them into a thin insulator layer in the transistor gate. The choice of insulator layer enhances the sensor's selectivity and sensitivity. The design includes an extended gate field-effect transistor, which separates the gate from the transistor, facilitating better integration with the fuel cell exhaust system. Small changes at the gate influence the drain-source current, enabling sensitive, label-free detection at the part-per-billion level. This innovative solution aims to provide effective monitoring of fuel cell membrane degradation, thereby improving the performance and durability of fuel cells.<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
|
47.084
|
1
|
4900
|
4900
|
2433734
|
{'FirstName': 'Dongmei', 'LastName': 'Dong', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dongmei Dong', 'EmailAddress': '[email protected]', 'NSF_ID': '000984270', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Rowan University', 'CityName': 'GLASSBORO', 'ZipCode': '080281700', 'PhoneNumber': '8562564057', 'StreetAddress': '201 MULLICA HILL RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NJ01', 'ORG_UEI_NUM': 'DMDEQP66JL85', 'ORG_LGL_BUS_NAME': 'ROWAN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Rowan University', 'CityName': 'GLASSBORO', 'StateCode': 'NJ', 'ZipCode': '080281700', 'StreetAddress': '201 MULLICA HILL RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NJ01'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433734.xml'}
|
Conference: 2025 Stochastic Physics in Biology GRC
|
NSF
|
09/01/2024
|
08/31/2025
| 20,000 | 20,000 |
{'Value': 'Standard Grant'}
|
{'Code': '03010000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'PHY', 'LongName': 'Division Of Physics'}}
|
{'SignBlockName': 'Krastan Blagoev', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924666'}
|
This award will partially support for a Gordon Research Conference (GRC) on Stochastic Physics in Biology, to be held in Ventura, CA, January 12-17, 2025. The meeting will bring together an outstanding and diverse group of physicists, mathematicians, engineers, and biologists at the forefront of research in the field of Stochastic Physics in Biology. The theme of the conference is “Bridging Theory and Experiments at all Scales.” The conference will address emerging challenges in understanding complex behaviors of biological systems using principles and theories in stochastic physics. The conference is preceded by a Gordon Research Seminar (GRS), a unique forum for graduate students, postdoctoral fellows, and other junior scientists to present new, unpublished research. The conference and GRS look exciting, timely, and in an area of interest to the POLS program at NSF. The program brings together leaders in the field, including researchers supported by POLS. <br/><br/>The conference is organized to optimize collaboration and communication among researchers from diverse disciplines. Sessions foster cross-disciplinary communication, by including speakers from different disciplines, with introductions by discussion leaders that bridge the different disciplines. The program is organized around nine sessions: I; Non-equilibrium Statistical Mechanics; II: Evolutionary Dynamics; III, Microbial Ecology; IV: Quantitative Physiology and Metabolism; V: Information Processing and Networks; VI: Cell Fate and Development; VII: Machine Learning and Causal Inference; VIII: Microbial Growth and Patterning; and IX: Molecular Organization. The program promotes networking through scheduled and informal discussion times, poster sessions, social hours, and Power Hour ™.<br/><br/>Broader impacts of this award include fostering interdisciplinary science, increase the diversity, equity, and inclusivity (DEI) of the Biological Physics Community, and the training and career development for early career researchers. This GRC has a longstanding commitment to diversity and inclusion and strongly believes they are an integral part of creating thriving communities that advance the frontiers of science for all scientists. GRC provides conference fellowships (such as the Carl Storm Underrepresented Minority and International Diversity Fellowships) to support the participation of U.S. underrepresented minorities. This GRC Stochastic Physics in Biology is committed to developing a diverse program and inclusive conference atmosphere. Participants will be selected to ensure proportional representation of women and underrepresented minorities. Of the 31 invited speakers, 60% are early- or mid-career, and 40% are women. In addition to invited talks, we will select from submitted abstracts another 20+ contributed talks, with a focus on underrepresented scientists and early- career researchers. To increase the participation of women and URM scientists at the meeting, we will reach out to known networks, including (1) the Society for the Advancement of Chicanos/Hispanics and Native Americans in Science (SACNAS), (2) the American Physical Society Inclusion, Diversity, and Equity Alliance (APS-IDEA), (3) Black in Biophysics, and (4) the Inclusive Graduate Education Network (IGEN). The Chair of this GRC conference, Dr. Andrew Mugler, participates in his department’s chapter of the APS Bridge Program, which actively targets admission and preparation of URM graduate students.<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
|
47.049
|
1
|
4900
|
4900
|
2433737
|
{'FirstName': 'Andrew', 'LastName': 'Mugler', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Andrew Mugler', 'EmailAddress': '[email protected]', 'NSF_ID': '000736211', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': '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': '724600', 'Text': 'PHYSICS OF LIVING SYSTEMS'}
|
2024~20000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433737.xml'}
|
Conference: A NSF/NIH Workshop on Neuromorphic Principles in Biomedicine and Healthcare
|
NSF
|
08/01/2024
|
07/31/2025
| 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': 'Ale Lukaszew', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928103'}
|
The goal of this workshop is to bring communities together to create a new generation of biomedical and neuro-engineering technologies that operate with extreme energy and data efficiency, adaptability, and performance advantages compared to current approaches. The plan is to congregate biomedical engineers, neural engineers, neuroscientists (computational and physiologists), neuromorphic scientists and engineers, materials scientists, clinicians, and mainstream engineers (e.g., electrical engineers, optical engineers, computer engineers, device engineers) to introduce new brain- and biology-inspired design principles to engineers who are currently investigating non-von Neumann architectures. It is expected that these new principles will provide alternative methods to solve relevant problems in the biomedical field, and to do so with significant improvements in the various metrics of the field. <br/><br/>The planned interactions will leverage the synergistic interests of the National Institutes of Health (NIH) [including the National Institute of Neurological Disorders and Stroke (NINDS) and the National Institute of Biomedical Imaging and Bioengineering (NIBIB)] and the National Science Foundation (NSF) to improve healthcare technologies, while also discovering fundamental concepts in engineering. An expected output of the workshop will be a neuromorphic biotechnology roadmap that articulates the benefits of the approach, highlights the challenges and proposes a potential pathway to achieve the benefits. We expect analysis of the needs of the field, presentation of emerging technologies and concepts, and their potential impact on the common interests of the NIH and NSF. This roadmap will clearly identify the near-term and longer-term opportunities and elucidate the potential partners – including the private sector – who should participate in driving these efforts. The 2-day workshop program will include 2 keynote addresses, 12 invited presentations, poster sessions for graduate student attendees, moderated discussion sessions and meetings with NIH and NSF program managers. It is also planned to invite the program committee, composed of 5 experts, to serve on discussion panels. A further group of 6 scholars/entrepreneur/innovator will be convened for this workshop. All of them will be encouraged to bring their students to participate in the discourse and present posters. In-person and virtual participants are expected.<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
|
47.041, 47.070
|
1
|
4900
|
4900
|
2433739
|
[{'FirstName': 'Jennifer', 'LastName': 'Blain Christen', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jennifer M Blain Christen', 'EmailAddress': '[email protected]', 'NSF_ID': '000519753', 'StartDate': '07/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Duygu', 'LastName': 'Kuzum', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Duygu Kuzum', 'EmailAddress': '[email protected]', 'NSF_ID': '000714781', 'StartDate': '07/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ralph', 'LastName': 'Etienne-Cummings', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ralph Etienne-Cummings', 'EmailAddress': '[email protected]', 'NSF_ID': '000360105', 'StartDate': '07/19/2024', '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': '089Y00', 'Text': 'FET-Fndtns of Emerging Tech'}, {'Code': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}, {'Code': '534200', 'Text': 'Disability & Rehab Engineering'}, {'Code': '756400', 'Text': 'CCSS-Comms Circuits & Sens Sys'}]
|
2024~100000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433739.xml'}
|
Travel: NSF Student Travel Grant for 2024 IEEE Conference on Communications and Network Security (IEEE CNS)
|
NSF
|
07/01/2024
|
06/30/2025
| 24,000 | 24,000 |
{'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': 'Dan Cosley', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928832'}
|
This award will support about 15 U.S.-based students' travel to the 2024 IEEE Conference on Communications and Network Security (IEEE CNS), which will be held in Taipei, Taiwan from September 30-October 3, 2024. The IEEE CNS conference is a premier venue for communications and network security researchers to present their latest research in a number of areas related to security and privacy. Student attendees will be able to present their ideas and projects to other attendees; this can them develop their communication and presentation skills, receive valuable feedback on their research from experts in the field, and expand their professional networks with researchers and industry professionals to get their insights on the latest technologies and challenges. Student attendance also enriches the conference itself, bringing new ideas and experiences into the community.<br/><br/>This travel award will provide career development and learning opportunities in IEEE CNS-related fields for U.S.-based students who would otherwise be less likely to be able to attend. Criteria for selection include a demonstrated interest in the field of communications and network security, as shown through research output, coursework, and/or project experience; need for financial support; and diversity of perspectives and backgrounds. The organizing team will widely advertise the availability of funding to increase the chance of reaching potential attendees from groups historically underrepresented in computing, with the twin goals of increasing the breadth of thoughts and perspectives available to conference attendees and developing the next generation of security and privacy researchers and practitioners.<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.
|
07/03/2024
|
07/03/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2433760
|
{'FirstName': 'Qiang', 'LastName': 'Zeng', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Qiang Zeng', 'EmailAddress': '[email protected]', 'NSF_ID': '000705200', 'StartDate': '07/03/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'George Mason University', 'CityName': 'FAIRFAX', 'ZipCode': '220304422', 'PhoneNumber': '7039932295', 'StreetAddress': '4400 UNIVERSITY DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_ORG': 'VA11', 'ORG_UEI_NUM': 'EADLFP7Z72E5', 'ORG_LGL_BUS_NAME': 'GEORGE MASON UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'H4NRWLFCDF43'}
|
{'Name': 'George Mason University', 'CityName': 'FAIRFAX', 'StateCode': 'VA', 'ZipCode': '220304422', 'StreetAddress': '4400 UNIVERSITY DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_PERF': 'VA11'}
|
{'Code': '806000', 'Text': 'Secure &Trustworthy Cyberspace'}
|
2024~24000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433760.xml'}
|
RI: Small: Bayesian Diffusion Models with Analysis-by-Synthesis
|
NSF
|
08/15/2024
|
07/31/2027
| 600,000 | 600,000 |
{'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': 'Jie Yang', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924768'}
|
Humans can perceive the three-dimensional world from a single two-dimensional image, even though such images do not contain explicit three-dimensional information. This capability in humans stems from two main factors: 1) the image of the three-dimensional world that matches the two-dimensional image content and 2) prior knowledge about the three-dimensional world. In statistics, this visual understanding process has traditionally been modeled using Bayesian inference, which combines the likelihood of something happening with a prior likelihood. However, this once prevailing theory has been challenged in the era of big data and deep learning, where three-dimensional understanding or inference is achieved by directly learning a mapping from two-dimensional images to the three-dimensional world. This award makes a timely effort by developing a new statistical inference technique, Bayesian Diffusion Models, which updates traditional Bayesian theory with a novel methodology to build advanced visual perception and cognition systems. As a general framework, the Bayesian Diffusion Model method is expected to have a profound impact on a wide range of tasks beyond visual perception.<br/><br/>The ever-increasing power of generative models presents an unprecedented opportunity to revisit the analysis-by-synthesis methodology by carefully integrating the generative prior into the learning and inference of the posterior. The data under study is becoming increasingly rich, encompassing images, language, and three-dimensional data. In such contexts, data-driven techniques alone are insufficient to fully capture the posterior. Furthermore, despite significant advances in generative modeling, the synthetic content produced by state-of-the-art generative models has not yet demonstrated its potential in broadly enhancing analysis and recognition tasks. Intuitively, rich augmentation from synthetic data should play an important role in improving these data-intensive analysis tasks. This project aims to bring scientific and engineering guidance in utilizing the synthetic data for the improvements to various computer vision applications, including both closed-world and open-world 3D reconstruction, policy learning, image classification, and scene understanding. The novel Bayesian Diffusion Model (BDM) framework, grounded in Bayesian theory, promises to serve as a new statistical tool for a wide array of tasks in computer vision, autonomous driving, robotics, human-computer interaction, and computational biology.<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
|
47.070
|
1
|
4900
|
4900
|
2433768
|
[{'FirstName': 'Zhuowen', 'LastName': 'Tu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zhuowen Tu', 'EmailAddress': '[email protected]', 'NSF_ID': '000083010', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Hao', 'LastName': 'Su', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hao Su', 'EmailAddress': '[email protected]', 'NSF_ID': '000758031', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'ZipCode': '920930021', 'PhoneNumber': '8585344896', 'StreetAddress': '9500 GILMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_ORG': 'CA50', 'ORG_UEI_NUM': 'UYTTZT6G9DT1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, SAN DIEGO', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'UNIVERSITY OF CALIFORNIA, SAN DIEGO', 'CityName': 'LA JOLLA', 'StateCode': 'CA', 'ZipCode': '920930515', 'StreetAddress': '9500 GILMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_PERF': 'CA50'}
|
{'Code': '749500', 'Text': 'Robust Intelligence'}
|
2024~600000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433768.xml'}
|
Pre-patterned Freestanding Single-crystalline Lithium Niobate Photonic Components for Advanced Quantum Photonic Integrated Circuits
|
NSF
|
09/01/2024
|
08/31/2027
| 390,000 | 390,000 |
{'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'}
|
Lithium niobate (LN), first synthesized 70 years ago, is highly valued in photonics for its excellent material properties and ability to facilitate frequency mixing across a broad spectrum, from gigahertz to petahertz frequencies. Recently, the commercial availability of thin-film LN has revitalized interest in the material due to its ability to promote tight mode confinement, thereby enhancing frequency-mixing efficiency and enabling new avenues for optical property optimization, such as dispersion engineering. This project seeks to develop pre-patterned freestanding single-crystalline LN photonic components for advanced quantum photonic integrated circuits. These components will serve as core elements in visible light communication platforms, offering superior performance compared to conventional materials. This work addresses significant challenges in the fabrication of thin-film LN, such as overcoming limitations of the smart-cut process and improving etching techniques. By advancing the integration of high-quality LN films, this project will promote scientific progress, enhance national technological capabilities, and support educational and diversity initiatives by involving K-12 and college-level students in hands-on experiments and workshops. This project will also benefit society by paving the way for advanced quantum photonics and communication technologies.<br/><br/>This project aims to develop pre-patterned freestanding single-crystalline LN photonic components to address the limitations of conventional LN fabrication techniques. The PI’s team has demonstrated a universal mechanical exfoliation method to produce freestanding single-crystalline membranes from complex-oxide materials. This project will build on that foundation to develop selective epitaxy of LN on pre-patterned substrates, achieving 100% yield exfoliation of damage-free LN waveguide patterns, and integrating these waveguides into photonic circuits for visible wavelength communication. Throughout the development, the project will precisely engineer photonic components to meet the stringent requirements of quantum photonics. Additionally, the team will optimize wafer-scale tailoring technology for high-density photonic components, advancing large-area quantum photonic platforms. Successful implementation of this technology will have a significant impact on the quantum photonics community by enabling damage-free, ultra-thin LN photonic components for visible wavelength communication. This addresses major limitations of conventional waveguides, such as poor optical confinement due to narrow bending radius and limited modulation capabilities. The project will also pioneer hybrid integration strategies for multiple photonic components, fostering unconventional functionalities and geometries in integrated platforms. Ultimately, this research will innovate photonic integration technology, advancing quantum processing and networking.<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
|
2433776
|
{'FirstName': 'Jeehwan', 'LastName': 'Kim', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jeehwan Kim', 'EmailAddress': '[email protected]', 'NSF_ID': '000726703', 'StartDate': '08/13/2024', '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': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}
|
2024~390000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433776.xml'}
|
Elements: An ML Ecosystem of Filament Detection: Classification, Localization, and Segmentation
|
NSF
|
01/01/2024
|
08/31/2025
| 598,489 | 426,388 |
{'Value': 'Standard Grant'}
|
{'Code': '05090000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'OAC', 'LongName': 'Office of Advanced Cyberinfrastructure (OAC)'}}
|
{'SignBlockName': 'Marlon Pierce', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927743'}
|
Since object-detection algorithms outperformed humans, one decade has passed. During this period, the unprecedented achievements of the Computer Vision domain made many believe that object detection is a solved problem. However, when it comes to scientific imagery such as microscopic, telescopic, aerial, satellite, and medical images, the general-purpose object-detection algorithms are far from perfect. A pixel-precise segmentation of objects and identification of their physical properties based on their texture features are still outstanding challenges in many interdisciplinary areas of research. Space Weather is one such area. Extreme space-weather events, similar to extreme terrestrial events, can have drastic economic and collateral impacts on mankind. Continuous and automatic monitoring of solar filaments plays an integral role in achieving reliable space-weather forecast/prediction systems, which consequently results in the technical preparedness much needed in many infrastructural aspects of the society, such as the power grid and the GPS systems. Our Machine Learning Ecosystem brings automatic, accurate, and reliable analyses of filaments’ dynamic behavior to the experts’ fingertips. The main contributions of this ecosystem are two data products of annotated filaments, and four software products which carry out the annotation (localization, identification, and segmentation) of these filaments. This modular ecosystem can be easily expanded in the future, beyond the lifetime of the award, as faster and more efficient modules are expected to be implemented by the community and replace the existing ones. Throughout the development of this project, we consult with the instrument/data experts from the National Solar Observatory (NSO) for proper utilization of the observation images and metadata we integrate from the six ground-based observatories of the Global Oscillation Network Group, that together provide a full-disk and continuous (24/7) coverage of the Sun.<br/><br/>The primary focus of this project is on the localization and segmentation of a specific solar event, called a filament, and the identification of its magnetic field chirality. That said, the novel concepts investigated in this project, such as the detection algorithm, the augmentation engine, and the segmentation loss function which is sensitive to granularities of objects, remain agnostic to the type of the event/object of interest. Moreover, the released datasets of annotated filaments can serve the Computer Vision community as a testbed for algorithms that aim at high-precision segmentation of objects. Our Machine Learning Ecosystem consists of two data products and four software products. The largest collection of manually annotated filaments data, and a continuously-growing collection of automatically annotated filaments are the two main data products. The main software products are (1) an augmentation engine that provides users with practically unlimited semi-real filament instances, (2) a deep neural network algorithm for localization, segmentation, and classification of filaments, (3) a high-precision segmentation loss function (sensitive to granularities of the observed filaments) that guides the segmentation task, and (4) a deployable detection module which carries out the localization, segmentation, and classification tasks in real time.<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.
|
05/24/2024
|
08/28/2024
|
None
|
Grant
|
47.050, 47.070
|
1
|
4900
|
4900
|
2433781
|
{'FirstName': 'Azim', 'LastName': 'Ahmadzadeh', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Azim Ahmadzadeh', 'EmailAddress': '[email protected]', 'NSF_ID': '000859306', 'StartDate': '05/24/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Missouri-Saint Louis', 'CityName': 'SAINT LOUIS', 'ZipCode': '631214400', 'PhoneNumber': '3145165897', 'StreetAddress': '1 UNIVERSITY BLVD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Missouri', 'StateCode': 'MO', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'MO01', 'ORG_UEI_NUM': 'GWCTP4CQ1E65', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MISSOURI SYSTEM', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Missouri-Saint Louis', 'CityName': 'SAINT LOUIS', 'StateCode': 'MO', 'ZipCode': '631214400', 'StreetAddress': '1 UNIVERSITY BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Missouri', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'MO01'}
|
[{'Code': '800400', 'Text': 'Software Institutes'}, {'Code': '807400', 'Text': 'EarthCube'}, {'Code': '808900', 'Text': 'Space Weather Research'}]
|
['2022~410386', '2024~16000']
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433781.xml'}
|
RINGS: WISECOM - Wireless Integrated Sensing, Learning and Communication Networks
|
NSF
|
01/01/2024
|
07/31/2025
| 793,985 | 609,876 |
{'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': 'Murat Torlak', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032920000'}
|
Future wireless networks will integrate sensing and communication functions. The sensing capabilities can come from the sensors of the devices in the network. The radio communication signal itself can also be used for sensing, especially when operating at high carrier frequencies, with high bandwidths and large antenna arrays. Examples are cellular networks supporting automated vehicles or industrial robots equipped with radar, lidar or cameras. This project advances the fundamental technologies, from a hardware and software perspective, to enable integrated sensing, learning and communication (ISLAC) wireless networks, capable of obtaining and communicating accurate information about the environment, relevant for the users and for the network operation itself. The sensing accuracy provided by these technologies is critical, both to support a given use case, and to enhance the resilience of the network, enabling a fast respond to failures or mis-configurations. The outcomes of this project will improve cellular connectivity for people and devices, by providing higher data rates, with more reliability, in a way that embraces machine learning and the wealth of sensor data also being deployed in such networks. <br/><br/>To establish the potential of integrated sensing, learning and communication networks to enhance their own resilience, this project develops: (a) the core enabling technologies for ISLAC networks, including hardware and signal processing algorithms for joint sensing and communications; (b) mathematical tools to measure resilience accounting for the particular propagation features and network operation at millimeter wave (mmWave) and sub-Terahertz (sub-THz) bands; (c) learning strategies that exploit sensing information to improve network adaptability; and (d) user-centric algorithms that exploit sensing information to improve network autonomy and increase. The developed strategies will be evaluated using a framework based on a combination of ray tracing, experimental measurements and models that mix the digital, physical, and virtual worlds. This methodology will enable the evaluation of the developed technologies in several relevant scenarios supported by cellular networks, including automated vehicles, automated factories, and immersive reality settings.<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.
|
06/10/2024
|
06/10/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2433782
|
{'FirstName': 'Nuria', 'LastName': 'Gonzalez Prelcic', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nuria Gonzalez Prelcic', 'EmailAddress': '[email protected]', 'NSF_ID': '000771932', 'StartDate': '06/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'ZipCode': '920930021', 'PhoneNumber': '8585344896', 'StreetAddress': '9500 GILMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_ORG': 'CA50', 'ORG_UEI_NUM': 'UYTTZT6G9DT1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, SAN DIEGO', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'StateCode': 'CA', 'ZipCode': '920930021', 'StreetAddress': '9500 GILMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_PERF': 'CA50'}
|
{'Code': '181Y00', 'Text': 'NextG Network Research'}
|
2022~609876
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433782.xml'}
|
Travel: Conference: Gateways 2024
|
NSF
|
08/01/2024
|
11/30/2025
| 32,251 | 32,251 |
{'Value': 'Standard Grant'}
|
{'Code': '05090000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'OAC', 'LongName': 'Office of Advanced Cyberinfrastructure (OAC)'}}
|
{'SignBlockName': 'Varun Chandola', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922656'}
|
Gateways 2024 is the major event for the science gateway community in the US to discuss challenges and solutions in the area, to identify new issues, to shape future directions for research, foster the exchange of ideas, standards and common requirements and push towards the wider adoption of science gateways. The topics covered by the Gateways conference series range from technical topics to use cases to related content such as usability or sustainability of science gateways. The knowledge transfer can be transformative between different research domains and technical content. The building blocks of science gateway frameworks are re-usable in diverse research areas evident in widely used frameworks such as Hubzero and Tapis. The Gateways conference series sets the stage for learning, engaging and empowering the different stakeholders in the community who are science gateway users, developers and providers as well as funders and decision makers. Providing travel grants for students and early-career researchers allows to include a diverse audience and support underrepresented minorities.<br/><br/>Science gateways are a key part of NSF funded Cyberinfrastructure, and they are used by hundreds of thousands of researchers and students, supporting both publication-quality science and at-scale education. Science gateways involve a comprehensive set of research domains that has a broad impact on society, addressing considerable challenges such as pandemics, climate change, global sustainability of food, water, and land use driven by growing populations and rising per capita incomes. In recognition of their importance, NSF has funded the Science Gateways Community Institute (SGCI) and more recently the SGX3 Science Gateways Center of Excellence to provide leadership for the science gateways community. The Gateways conference series is one of the of flagships of SGCI and SGX3 and the major event in the US to bring the science gateways community together. The conference series has existed since 2016 and has attracted each year between 100-170 participants. In 2023 it has moved from an SGX3-organized conference to a community-driven conference with the first time the general chair being selected by a newly established advisory board for the conference and who is not part of the SGCI/SGX3 team. The goal is to attract additional research domains and tap into the chair's networks that are not already in contact with SGCI/SGX3. SGX3 continues to guide the conference while inviting each year since 2023 a different general chair. Gateways 2024 features various program formats such as keynotes, presentations, tutorials, demos, panels, posters and Bring Your Own Portal. Accepted submissions are published in open-access proceedings and accepted papers are invited to a special issue in a journal. SGCI/SGX3 has an impressive record of underrepresented minority involvement within the science gateway community. The travel grant allows to involve more students and early-career researchers at Gateways 2024 and they are selected under consideration 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
|
2433784
|
{'FirstName': 'Sandra', 'LastName': 'Gesing', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sandra Gesing', 'EmailAddress': '[email protected]', 'NSF_ID': '000669642', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'ZipCode': '920930021', 'PhoneNumber': '8585344896', 'StreetAddress': '9500 GILMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_ORG': 'CA50', 'ORG_UEI_NUM': 'UYTTZT6G9DT1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, SAN DIEGO', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'StateCode': 'CA', 'ZipCode': '920930021', 'StreetAddress': '9500 GILMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_PERF': 'CA50'}
|
{'Code': '736100', 'Text': 'EDUCATION AND WORKFORCE'}
|
2024~32251
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433784.xml'}
|
Conference: CRCNS PI Meeting 2024
|
NSF
|
08/15/2024
|
07/31/2025
| 41,785 | 41,785 |
{'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': 'Kenneth Whang', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032925149'}
|
The Collaborative Research in Computational Neuroscience (CRCNS) program supports a broad spectrum of investigators advancing computational understanding of nervous system structure and function, mechanisms underlying nervous system disorders, and computational strategies used by the nervous system. The goal of this meeting of CRCNS Principal Investigators is to foster interaction and collaboration across this vibrant community, highlighting the intellectual advances and broader impacts of CRCNS awardees. The meeting, scheduled for Aug. 20-21, 2024 in Minneapolis, Minnesota, is hosted by the University of Minnesota and includes poster presentations, talks, and plenary lectures, covering all areas of computational neuroscience represented by funded projects in the program. The meeting will include projects involving the United States, France, Germany, Israel, Japan, and Spain, sponsored by NSF and eight other partner agencies.<br/><br/>This international meeting should have a significant impact on the participants and the future of the CRCNS program. The meeting results are likely to include new research directions that will be publicized to the research community through publications and the meeting website. The results dissemination should inform and the CRCNS research community in their transdisciplinary collaboration, educational activities, and spur other innovative research directions. The broader impacts of the meeting are to facilitate progress in the field and stimulate conversations, connections, and collaborations that will lead toward better informed and effective CRCNS research and resulting technologies for the broadest possible user populations.<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
|
2433785
|
{'FirstName': 'Alexander', 'LastName': 'Opitz', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Alexander Opitz', 'EmailAddress': '[email protected]', 'NSF_ID': '000741715', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Minnesota-Twin Cities', 'CityName': 'MINNEAPOLIS', 'ZipCode': '554552009', 'PhoneNumber': '6126245599', 'StreetAddress': '200 OAK ST SE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Minnesota', 'StateCode': 'MN', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MN05', 'ORG_UEI_NUM': 'KABJZBBJ4B54', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MINNESOTA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Regents of the University of Minnesota', 'CityName': 'Minneapolis', 'StateCode': 'MN', 'ZipCode': '554552009', 'StreetAddress': 'Nils Hasselmo Hall, 312 Church St SE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Minnesota', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'MN05'}
|
{'Code': '732700', 'Text': 'CRCNS-Computation Neuroscience'}
|
2024~41785
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433785.xml'}
|
Travel: NSF Student Travel Grant for the 2024 IEEE-EMBS International Conference on Body Sensor Networks (IEEE BSN)
|
NSF
|
07/15/2024
|
06/30/2025
| 20,000 | 20,000 |
{'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': 'Goli Yamini', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032925367'}
|
This project is to support student travel at the 2024 IEEE-EMBS International Conference on Body Sensor Networks (BSN 2024). BSN is the premier conference in the areas of sensors and systems for digital health. It will bring together leaders and experts in academia, industry, healthcare, and non-profit organizations and provide a cross-disciplinary, highly selective, and single-track forum for cutting-edge research related to devices and sensors, hardware and software systems, predictive models, and data analytics in the healthcare/medical domains. Student participants will also have opportunities to receive professional support and career advice from internationally recognized experts. Travel support increases engagement with the research community and provides professionally significant opportunities to students who might otherwise not able to attend the conference.<br/><br/>This project aims to increase the accessibility of the scientific forum that is BSN 2024 such that students may explore their interests, interact and network with seasoned professionals, and identify the various career paths available within the broader community of health scientists and technologists. With this award, students who would otherwise find conference registration fees and travel expenses prohibitive can obtain these benefits. The 2024 International Conference on Body Sensor Networks will focus on cutting-edge innovations in sensor technologies, nascent applications of artificial intelligence in medical science, and issues of social responsibility that emerge as digital medicine evolves. Increasing student engagement through the reduction of expenses, this award not only makes access to a premier international scientific conference more equitable, it also constitutes an investment in the future of the medical sensor research community; a community that is critical to the next generation of healthcare.<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.
|
07/12/2024
|
07/12/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2433786
|
{'FirstName': 'Nabil', 'LastName': 'Alshurafa', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nabil Alshurafa', 'EmailAddress': '[email protected]', 'NSF_ID': '000718284', 'StartDate': '07/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Northwestern University at Chicago', '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': 'KG76WYENL5K1', 'ORG_LGL_BUS_NAME': 'NORTHWESTERN UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'KG76WYENL5K1'}
|
{'Name': 'Northwestern University at Chicago', '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': '748400', 'Text': 'IIS Special Projects'}
|
2024~20000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433786.xml'}
|
Enhancing Organic Chemistry Education: Acquisition of a Desktop Mass Spectrometer and Nuclear Magnetic Resonance Spectrometer
|
NSF
|
01/01/2025
|
12/31/2025
| 197,968 | 197,968 |
{'Value': 'Standard Grant'}
|
{'Code': '11040100', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DUE', 'LongName': 'Division Of Undergraduate Education'}}
|
{'SignBlockName': 'Mike Ferrara', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922635'}
|
With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI Program), this Educational Instrumentation project at Suffolk Community College, a two-year institution in New York, will strengthen undergraduate learning and experiences in organic chemistry. Specifically, this project will secure a desktop Mass Spectrometer (MS) and a Nuclear Magnetic Resonance spectrometer (NMR), which will allow students to engage in hands-on learning in Organic Chemistry I and II courses. An estimated 100 students will utilize the project-funded equipment each year. In addition to providing improved experiences in chemistry courses, the new equipment will also be used by student clubs and as part of public outreach and recruiting events at the institution. <br/><br/>The goals of this project are to enrich the learning and experiences of undergraduate students by providing critical equipment in chemistry. Students in pre-professional programs and pursuing degrees in chemistry and biology will be able to improve their practical skills in modern laboratory techniques and enhance their understanding of chemical structures and reactions. Exposure to MS and NMR techniques will provide a modern learning experience and improve their competitiveness for the workforce and transfer to 4-year institutions. The project will assess the impact of the project-funded equipment through consideration of equipment usage rates and costs, student success in the organic chemistry courses, performance in impacted laboratory courses, and artifacts from project-related faculty professional development opportunities. This project is funded by the HSI Program, which aims to enhance undergraduate STEM education, broaden participation in STEM, and increase capacity to engage in the development and implementation of innovations to improve STEM teaching and learning at HSIs.<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
|
2433790
|
[{'FirstName': 'Michael', 'LastName': 'England', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michael England', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A03YV', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Keith', 'LastName': 'Baessler', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Keith Baessler', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A03DC', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Suffolk Community College', 'CityName': 'SELDEN', 'ZipCode': '117842851', 'PhoneNumber': '6314514760', 'StreetAddress': '533 COLLEGE RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NY01', 'ORG_UEI_NUM': 'FLKPSYMY25H1', 'ORG_LGL_BUS_NAME': 'SUFFOLK COUNTY COMMUNITY COLLEGE', 'ORG_PRNT_UEI_NUM': 'FLKPSYMY25H1'}
|
{'Name': 'Suffolk Community College', 'CityName': 'SELDEN', 'StateCode': 'NY', 'ZipCode': '117842851', 'StreetAddress': '533 COLLEGE RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NY01'}
|
{'Code': '077Y00', 'Text': 'HSI-Hispanic Serving Instituti'}
|
2024~197968
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433790.xml'}
|
Collaborative Research: SaTC: EDU: Authentic Learning of Machine Learning in Cybersecurity with Portable Hands-on Labware
|
NSF
|
12/15/2023
|
08/31/2025
| 279,844 | 166,696 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Ambareen Siraj', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928182'}
|
This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).<br/><br/>As cybersecurity threats grow in complexity, the burden of responding to these threats also increases. Early detection of security vulnerabilities and threats is needed. Machine learning (ML) approaches enable the analysis of large amounts of data and could be used to predict and prevent future cybersecurity threats. This project will enhance the cybersecurity curricula across computing disciplines using an authentic learning approach. Authentic learning approaches engage students’ active learning and problem-solving capabilities by using hands-on approaches and real-world topics. This approach has been increasingly popular for teaching cybersecurity but is less commonly used to teach ML in cybersecurity. The project will design and develop ten portable labware modules that will support a broad audience to learn ML in cybersecurity effectively and result in more efficient student engagement. The resources developed will support authentic learning of cybersecurity topics, and increase student learning and interests as well as faculty collaboration between Kennesaw State University and Tuskegee University. The project will disseminate the resources via faculty workshops, conference publications, and webinars.<br/><br/>The design of the proposed learning modules will be based on popular machine learning algorithms and publicly available free datasets related to common cybersecurity problems such as Denial of Service, CAPTCHA bypassing, and SQL Injection attacks. The modules will be deployed on the open-source Google CoLaboratory (CoLab) environment. Learners will access and practice all labs interactively using a browser anywhere and anytime without a need for time-consuming installation and configuration. The hands-on labs will provide students with step-by-step interactive activities to learn ML models in the CoLab environment, followed by testing of models. The project will seek to answer the following research questions: (i) Do innovative, authentic learning-based ML in cybersecurity resources increase learners’ knowledge and interest in solving real-world problems and careers in the cybersecurity workforce? (ii) Does the hands-on labware developed by the project impact students’ grades, learning, attitudes, motivation, and self-efficacy towards ML in cybersecurity? (iii) What is the relationship between students’ motivation and ML in cybersecurity learning? (iv) Do participating faculty perceive the ML in cybersecurity authentic learning resources as effective in engaging diverse, underrepresented students in cybersecurity? The project evaluation will use a mixed-methods design and administrative data, focus groups, and survey data. The quantitative and qualitative data generated from these sources will be used for formative and summative assessments. <br/><br/>This project is supported by the Secure and Trustworthy Cyberspace (SaTC) program, which funds proposals that address cybersecurity and privacy, and in this case specifically cybersecurity education. The SaTC program aligns with the Federal Cybersecurity Research and Development Strategic Plan and the National Privacy Research Strategy to protect and preserve the growing social and economic benefits of cyber systems while ensuring security and privacy.<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
|
47.076
|
1
|
4900
|
4900
|
2433800
|
{'FirstName': 'Hossain', 'LastName': 'Shahriar', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hossain Shahriar', 'EmailAddress': '[email protected]', 'NSF_ID': '000630552', 'StartDate': '06/17/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of West Florida', 'CityName': 'PENSACOLA', 'ZipCode': '325145750', 'PhoneNumber': '8504742825', 'StreetAddress': '1100 UNIVERSITY PKWY BLDG 20E 10', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'FL01', 'ORG_UEI_NUM': 'WHXVFCB1F1E3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WEST FLORIDA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of West Florida', 'CityName': 'PENSACOLA', 'StateCode': 'FL', 'ZipCode': '325145732', 'StreetAddress': '11000 UNIVERSITY PKWY BLDG 10', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'FL01'}
|
{'Code': '166800', 'Text': 'CYBERCORPS: SCHLAR FOR SER'}
|
2021~166696
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433800.xml'}
|
I-Corps: Translation Potential of a Tool to Address the Challenges of Working with Unfamiliar Software Code
|
NSF
|
09/01/2024
|
02/28/2025
| 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': 'Molly Wasko', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924749'}
|
The broader impact of this I-Corps project is based on the development of a tool that improves the understanding and documentation of software design. As technology advances, the demand for efficient and maintainable software grows; This tool addresses the critical need for developers to understand unfamiliar code. Working with unfamiliar code is a significant challenge for engineers when onboarding to a project, working with old legacy code, and when collaborating with globally distributed teams. By enabling developers to comprehend and adapt to codebases rapidly, this tool enhances collaboration, accelerates development timelines, and reduces errors, ultimately lowering costs for businesses. The potential societal and commercial impact include reducing the tedious and challenging work with unfamiliar code that slows the development process and increasing the ability of companies and organizations of all sizes to release software and new features to their users faster and at lower cost. <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. The solution is based on the development of an innovative tool that offers a new form of documentation for software engineers working with unfamiliar code. Traditional documentation methods often fail to keep up with changes in the codebase, leading software documentation to be distrusted or unused by engineers in practice. This tool integrates static analysis tools into developers’ workflows to enable the design to be synchronized with the code. Built on top of a new way of documenting code through design rules that are checked against the code, the tool offers documentation that is always up-to-date, offers information when developers need it, and guides developers in writing code.<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
|
2433803
|
{'FirstName': 'Thomas', 'LastName': 'LaToza', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Thomas LaToza', 'EmailAddress': '[email protected]', 'NSF_ID': '000637316', 'StartDate': '07/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'George Mason University', 'CityName': 'FAIRFAX', 'ZipCode': '220304422', 'PhoneNumber': '7039932295', 'StreetAddress': '4400 UNIVERSITY DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_ORG': 'VA11', 'ORG_UEI_NUM': 'EADLFP7Z72E5', 'ORG_LGL_BUS_NAME': 'GEORGE MASON UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'H4NRWLFCDF43'}
|
{'Name': 'George Mason University', 'CityName': 'FAIRFAX', 'StateCode': 'VA', 'ZipCode': '220304422', 'StreetAddress': '4400 UNIVERSITY DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_PERF': 'VA11'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433803.xml'}
|
Conference: A Virtual Workshop for Building Leadership Capacity to Support Two-Year College and Disciplinary Society Collaborations
|
NSF
|
10/01/2024
|
09/30/2025
| 98,283 | 98,283 |
{'Value': 'Standard Grant'}
|
{'Code': '11040000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DUE', 'LongName': 'Division Of Undergraduate Education'}}
|
{'SignBlockName': 'Kalyn Owens', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924615'}
|
This project aims to serve the national interest by strengthening the connection between two-year college faculty and their respective disciplinary societies, something both groups have been striving to achieve. There is a critical need for the development of a core group of leaders to enact sustainable change that will enhance these connections. This project will facilitate and evaluate a virtual, multi-day workshop with a focus on leadership development that will include teams of two-year college faculty and disciplinary society representatives. Eleven disciplines will participate. The first part of the workshop will include sessions on specific leadership skills and planning for participant-led outreach activities to put those skills into practice, with opportunities for cross-discipline sharing. These outreach activities for their two-year college and disciplinary society colleagues will include workshops offered at their campus, in their region, and at disciplinary society conferences as well as individual meetings with administrators. Building on their disciplinary action plans, the outreach activities will engage people beyond the workshop participants and communicate the benefits of two-year college engagement with societies. In the last part of the workshop, participants will report on their outreach activities and discuss next steps. The leadership capacities gained and practiced in this workshop will contribute to the broader STEM enterprise by empowering the participants to be agents of change on campus, in their disciplinary societies, and in cross-disciplinary efforts. <br/><br/>The project will foster engagement between two-year colleges and disciplinary societies, strengthen connections between two-year college faculty and their disciplinary communities, and support sharing of effective strategies across multiple disciplines and disciplinary societies. The workshop goals are to (1) provide leadership development that supports participants in advancing in leadership roles needed to promote two-year-college and disciplinary society collaborative efforts; (2) support participants in leading outreach activities that build on disciplinary action plans and communicate the benefits of two-year college-disciplinary society engagement; (3) build networks and communities of participants within and across disciplines; and (4) investigate the impact of this leadership development in moving collaborations between two-year colleges and disciplinary societies forward. This project will advance knowledge of effective strategies for enhancing collaborations between two-year colleges and disciplinary societies through an analysis of the outreach activities led by participants. This project will also advance knowledge of how the workshop influenced participant leadership development and confidence using pre- and post-surveys. A workshop report will be distributed to all participants and disciplinary societies and will be available to all in the professional and academic scientific community on the workshop website. A practice brief will be shared with organizations for two-year colleges and administrators. The NSF IUSE: Innovation in Two-Year College STEM Education (ITYC) Program seeks to accelerate the impact of and advance knowledge about emerging and evidence-based practices in undergraduate STEM education at two-year colleges.<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
|
47.076
|
1
|
4900
|
4900
|
2433814
|
[{'FirstName': 'Mark', 'LastName': 'Maier', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mark H Maier', 'EmailAddress': '[email protected]', 'NSF_ID': '000430966', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ellen', 'LastName': 'Iverson', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ellen Iverson', 'EmailAddress': '[email protected]', 'NSF_ID': '000335972', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Pamela', 'LastName': 'Eddy', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Pamela L Eddy', 'EmailAddress': '[email protected]', 'NSF_ID': '000701019', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ruth', 'LastName': 'Macdonald', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ruth H Macdonald', 'EmailAddress': '[email protected]', 'NSF_ID': '000418539', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Carleton College', 'CityName': 'NORTHFIELD', 'ZipCode': '550574001', 'PhoneNumber': '5072224303', 'StreetAddress': '1 N COLLEGE ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Minnesota', 'StateCode': 'MN', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'MN02', 'ORG_UEI_NUM': 'KALKKJL418Q7', 'ORG_LGL_BUS_NAME': 'CARLETON COLLEGE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Carleton College', 'CityName': 'NORTHFIELD', 'StateCode': 'MN', 'ZipCode': '550574001', 'StreetAddress': '1 N COLLEGE ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Minnesota', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'MN02'}
|
{'Code': '264Y00', 'Text': 'Innov TwoYear College STEM Ed'}
|
2024~98283
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433814.xml'}
|
EAGER: Approaches to Sustainability and Resiliency using Competitive Analysis
|
NSF
|
10/01/2024
|
09/30/2026
| 299,713 | 299,713 |
{'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': 'Peter Brass', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922182'}
|
The project aims to find new algorithmic methods for the resilient integration of renewable energy into the electrical grid as well as for making transportation more sustainable. For example, in the traditional energy grid, when renewables produce a surplus of energy, such surplus generally does not affect the operation of traditional power plants. Instead, renewables are throttled down, or the surplus is simply ignored. However, in the future, when most of the power is generated by renewables, this will not be tenable. Rather, traditional power plant output needs to be throttled down or switched off in response to less predictable renewable supplies. On the demand side, power usage has also become less predictable with the switch from gas or electric-resistive heating to heat pumps, independent solar panels, the adoption of electric vehicles, and more diverse working hour patterns. With transportation, the transition to electric and autonomous vehicles, as well as multi-modal transportation, is underway and fueled by a smart grid built around renewable energy. Rather than using statistical methods, this project pursues a game-theoretic approach. In the online setting, one imagines the input to be created by an omniscient adversary who knows the code of the online algorithm and strives to defeat the algorithm. An online algorithm with good competitiveness gives a performance guarantee relative to the best that could be done if one knew the future. Thus, it makes good decisions even in situations where the input derives from unusual or unexpected circumstances, such as supply chain disruptions due to disasters. The project will also create more sustainable solutions through algorithms related to batching and server problems in datacenters. The project will also train students and broaden participation in computing as it is hosted at the University of Nevada, Las Vegas, a minority-serving institution ranked as one of the most diverse universities for undergraduates. <br/><br/>Power plant cycling can be avoided by the obvious method of not cycling a unit, and that may include staying on at a loss; this tradeoff is modeled by abstracting the problem as a power-down problem in the online competitive setting. The project seeks to design novel online competitive algorithms for the power-down problem. A "decrease and reset" scheme is considered where competitiveness is relaxed by a small amount to allow for online competitive algorithms that are close to optimal yet with better performance in many types of request sequences. The project also includes consideration of new potential-guided methods, as well as the study of continuous power-down problems. The use of online models opens a new approach to benefit future transportation systems. Models for car-sharing systems, for example, are inherently online. A problem complementary to both power-down as well as transportation is the server problem. The project includes the study of several open questions around online server problems. Competitive algorithms for the delayed server problem for modeling car sharing, battery consolidation systems and traffic signal control are also sought. The investigator heads the University of Nevada Las Vegas Center for Information Technology and Algorithms; the award contributes to further establishing and nurturing the important work being done at this center.<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
|
2433820
|
[{'FirstName': 'Wolfgang', 'LastName': 'Bein', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Wolfgang Bein', 'EmailAddress': '[email protected]', 'NSF_ID': '000466300', 'StartDate': '07/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Lawrence', 'LastName': 'Larmore', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lawrence L Larmore', 'EmailAddress': '[email protected]', 'NSF_ID': '000306964', 'StartDate': '07/22/2024', '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': '891544019', 'StreetAddress': '4505 S MARYLAND PKWY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Nevada', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NV01'}
|
[{'Code': '287800', 'Text': 'Special Projects - CCF'}, {'Code': '779600', 'Text': 'Algorithmic Foundations'}]
|
2024~299713
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433820.xml'}
|
STEM-APWD: Access and Equity in STEM: Disability and Innovation in Fundamental Research
|
NSF
|
07/01/2024
|
12/31/2024
| 93,265 | 93,265 |
{'Value': 'Standard Grant'}
|
{'Code': '04050000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SES', 'LongName': 'Divn Of Social and Economic Sciences'}}
|
{'SignBlockName': 'Lee Walker', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927174'}
|
The overall goals of this conference is to spotlight the kinds of research that disabled investigators are conducting, to highlight ways that disabilities can lead to innovation in research materials, methods, and findings, to discuss the kinds of accessibility challenges and systemic ableism faced by researchers with disabilities at every stage of the research process. The conference will also suggest ways to engage the scientific community in working to overcome challenges and to promote access, equity, and inclusion in fundamental research for disabled investigators. It will highlight both the excellent science that is done by investigators with disabilities, and the means by which excluded individuals may be better supported in STEM. The conference will improve collaboration within and across career stages, fields, and institutions, and between investigators with and without disabilities.<br/><br/>This conference centers the work, perspectives, and lived experiences of researchers with disabilities, in order to initiate a focus in various scientific communities on increasing equitable participation of persons with disabilities in fundamental research. The conference will take place on July 10, 2024 at NSF headquarters in Alexandria, VA, in hybrid format to ensure maximal access to persons with disabilities. It will consist of two panels of 5 invited panelists each. All invited panelists are STEM researchers with various types of disabilities who work in a range of academic disciplines. The first panel seeks to spotlight examples of the kinds of research that disabled investigators are conducting. The second panel focuses on researchers with disabilities who are working on projects to specifically promote access, equity, and inclusion in STEM fields. These conversations will facilitate more inclusive and representative scholarship across disabilities, and will facilitate direct discussion with scientific communities, leadership, and staff. Community awareness and understanding should result in improved policies and opportunities for scientists with disabilities and the communities that engages with them.<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.
|
06/18/2024
|
06/18/2024
|
None
|
Grant
|
47.075
|
1
|
4900
|
4900
|
2433830
|
[{'FirstName': 'Siobhán', 'LastName': 'Cully', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Siobhán M Cully', 'EmailAddress': '[email protected]', 'NSF_ID': '000201205', 'StartDate': '06/18/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Caroline', 'LastName': 'Solomon', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Caroline M Solomon', 'EmailAddress': '[email protected]', 'NSF_ID': '000073108', 'StartDate': '06/18/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Robert', 'LastName': 'Englebretson', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robert Englebretson', 'EmailAddress': '[email protected]', 'NSF_ID': '000504949', 'StartDate': '06/18/2024', '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': '118Y00', 'Text': 'Security & Preparedness'}
|
2024~93265
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433830.xml'}
|
I-Corps: Translation potential of non-contact monitoring of human vital signs
|
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 non-contact health monitoring method with broad applications. The solution has the potential to seamlessly monitor vital signs without requiring users to wear any devices. Unlike wired systems, this technology offers convenience, reliability, and long-term monitoring, benefiting both healthcare providers and individuals seeking advanced care. In addition to targeting diseases like sleep apnea and sudden infant death syndrome, the technology also promises innovation in motion-adaptive cancer radiotherapy. The technology can potentially revolutionize patient care, reducing costs, and improving outcomes, especially for vulnerable populations.<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 advanced beamforming that supports concurrent multiple target sensing and tracking of human subjects. This technology includes the use of advanced signal processing algorithms that enable high sensitivity and a wide dynamic range for the detection of micro-motions. The technology considers a coherent detection architecture that supports multiple operation modes for high dynamic range. Finally, the solution includes an antenna-in-package for the integration of the system with compact size, low cost, and high performance.<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
|
2433836
|
{'FirstName': 'Changzhi', 'LastName': 'Li', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Changzhi Li', 'EmailAddress': '[email protected]', 'NSF_ID': '000545895', 'StartDate': '06/17/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Texas Tech University', 'CityName': 'LUBBOCK', 'ZipCode': '79409', 'PhoneNumber': '8067423884', 'StreetAddress': '2500 BROADWAY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_ORG': 'TX19', 'ORG_UEI_NUM': 'EGLKRQ5JBCZ7', 'ORG_LGL_BUS_NAME': 'TEXAS TECH UNIVERSITY SYSTEM', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Texas Tech University', 'CityName': 'LUBBOCK', 'StateCode': 'TX', 'ZipCode': '79409', 'StreetAddress': '2500 BROADWAY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_PERF': 'TX19'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433836.xml'}
|
Planning: The Valparaiso University Research Collaboratory: A Needs Assessment and Pilot Project
|
NSF
|
08/15/2024
|
07/31/2025
| 99,963 | 99,963 |
{'Value': 'Standard Grant'}
|
{'Code': '01060000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OIA', 'LongName': 'OIA-Office of Integrative Activities'}}
|
{'SignBlockName': 'Dina Stroud', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032925015'}
|
This planning project aims to investigate and inform strategies for creating a new centralized administrative division at Valparaiso University, which will enable the University to effectively seek, secure, and sustain mutually beneficial research partnerships within regional industries. As a scalable model to be shared with small universities across the nation, the "Research Collaboratory" has the potential to diversify and strengthen the national research enterprise by increasing participation among primarily undergraduate universities. In addition to enhancing faculty research opportunities, enriching student learning, and encouraging interdisciplinary collaboration at the institution, the university-industry partnerships made possible by this project will provide STEM workforce development opportunities and promote economic growth. <br/><br/>An advisory council will be formed to oversee progress toward the two primary goals of the Valparaiso University Research Collaboratory planning project. First, a comprehensive assessment will be performed to quantify and qualify the current need and potential for partnerships. Industry opportunities and challenges will be considered within the context of faculty capabilities and interests in order to prioritize general topics and specific entities to pursue for near-future research partnerships. Second, a pilot project will be launched within a discrete field or topic of inquiry in order to explore organizational and logistical best practices, which will later be expanded to all academic STEM disciplines. Observations and lessons learned will be carefully documented to enable thorough dissemination at the conclusion of the 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.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.083
|
1
|
4900
|
4900
|
2433851
|
[{'FirstName': 'Kevin', 'LastName': 'Goebbert', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kevin H Goebbert', 'EmailAddress': '[email protected]', 'NSF_ID': '000728222', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Marie', 'LastName': 'Foster-Bruns', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Marie Foster-Bruns', 'EmailAddress': '[email protected]', 'NSF_ID': '000957734', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Kelly', 'LastName': 'Anthony', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kelly M Anthony', 'EmailAddress': '[email protected]', 'NSF_ID': '000961073', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Valparaiso University', 'CityName': 'VALPARAISO', 'ZipCode': '463834520', 'PhoneNumber': '2194645215', 'StreetAddress': '1700 CHAPEL DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Indiana', 'StateCode': 'IN', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'IN01', 'ORG_UEI_NUM': 'Q6VQBGLLB2J4', 'ORG_LGL_BUS_NAME': 'LUTHERAN UNIVERSITY ASSOCIATION INC', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Valparaiso University', 'CityName': 'VALPARAISO', 'StateCode': 'IN', 'ZipCode': '463834520', 'StreetAddress': '1700 CHAPEL DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Indiana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'IN01'}
|
{'Code': '221Y00', 'Text': 'GRANTED'}
|
2024~99963
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433851.xml'}
|
I-Corps: Translation Potential of Stabilized Chitosan Tissue Regeneration Materials
|
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': 'Ruth Shuman', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922160'}
|
The broader impact of this I-Corps project is the development of a biomaterial for bone graft regeneration. A major obstacle to the effectiveness of bone grafting procedures is the overgrowth or invasion of fibrous tissues, which grow into the graft site faster than the healing bone. Currently, guided bone regeneration (GBR) membranes are commonly used to augment healing by covering and protecting bone grafted spaces during the bone regeneration process. However, current GBR membranes suffer a high incidence of failure due to rapid degradation, infection, and poor barrier properties, leading to revision surgeries and additional costs to patients and the healthcare system. This technology uses nanofiber materials that are electrospun from chitosan, a biopolymer obtained from natural sources such as shrimp shells and fungi. The use of natural, degradable materials serves as a more sustainable and biocompatible alternative to currently used synthetic polymers such as polytetrafluoroethylene and natural materials such as collagen, which have unpredictable degradation rates and high susceptibility to contamination. The chitosan nanofibers have material characteristics that may reduce early degradation, bacterial attachment, and soft tissue ingrowth, which may improve patient outcomes. In addition to bone graft regeneration, chitosan nanofibers may be used for wound healing dressings, food packaging materials, and local therapeutic delivery.<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 stabilized chitosan nanofiber materials for guiding tissue regeneration. The technology uses chemical techniques to covalently bond a fatty acid to functional groups in the chitosan biopolymer, which allows for the stabilization of fibers without swelling or degradation during the fabrication process. The nanofiber structure forms a porous structure ideal for nutrient exchange while remaining cell occlusive, allowing appropriate healing and providing the needed barrier function. The stabilizing fatty acids prevent swelling of the fibers and solve the problem of early degradation of resorbable membranes. As the chitosan membrane does eventually degrade, its non-acidic degradation products do not produce the inflammation associated with synthetic materials and may promote healing and resolution of inflammation. In preclinical evaluations, these nanofiber membranes have been shown to promote bone growth, guide inflammation resolution, deliver therapeutics including anti-inflammatory molecules and antimicrobials, provide a barrier to separate tissue compartments, and prevent bacterial colonization without limiting nutrient exchange.<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
|
47.084
|
1
|
4900
|
4900
|
2433852
|
{'FirstName': 'Jessica', 'LastName': 'Jennings', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jessica A Jennings', 'EmailAddress': '[email protected]', 'NSF_ID': '000500067', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Memphis', 'CityName': 'MEMPHIS', 'ZipCode': '381520001', 'PhoneNumber': '9016783251', 'StreetAddress': '115 JOHN WILDER TOWER', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Tennessee', 'StateCode': 'TN', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'TN09', 'ORG_UEI_NUM': 'F2VSMAKDH8Z7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MEMPHIS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Memphis', 'CityName': 'MEMPHIS', 'StateCode': 'TN', 'ZipCode': '381520001', 'StreetAddress': '115 JOHN WILDER TOWER', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Tennessee', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'TN09'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433852.xml'}
|
I-Corps: Translation potential of electromagnetic wave manipulation to enhance magnetic resonance imaging systems
|
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 advanced technologies to enhance magnetic resonance imaging systems. This innovation aims to significantly improve the safety and quality of imaging, particularly benefiting patients with metal-based medical implants. By reducing the dependency on high refractive indices materials and simplifying the system architecture, the technology can lower operational costs, making high-quality diagnostic imaging more accessible and safer. This advance promises to address critical gaps in current medical diagnostic capabilities, opening high-quality imaging to a broader market, including resource-limited and rural areas. Preliminary market surveys indicate a strong demand for safer, more efficient imaging solutions, highlighting the technology's potential to transform healthcare diagnostics and improve patient outcomes.<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 a dual-layer design tailored for magnetic resonance imaging systems. The technology finely tunes and manipulates electromagnetic waves, enabling in situ adjustments to adapt to different imaging configurations seamlessly. Initial research has demonstrated that this design can enhance image quality and safety in high magnetic field systems, providing a significant improvement over current technologies. Experimental setups have validated the feasibility of the solution, indicating its potential to achieve high diagnostic accuracy while shortening scan times and ensuring patient safety.<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.
|
06/25/2024
|
06/25/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2433854
|
{'FirstName': 'Aleksandr', 'LastName': 'Krasnok', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Aleksandr Krasnok', 'EmailAddress': '[email protected]', 'NSF_ID': '000801139', 'StartDate': '06/25/2024', 'EndDate': None, 'RoleCode': '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': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433854.xml'}
|
The Educational Alliance for Semiconductor Experiential Learning
|
NSF
|
10/01/2024
|
09/30/2028
| 4,697,075 | 4,697,075 |
{'Value': 'Standard Grant'}
|
{'Code': '11040100', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DUE', 'LongName': 'Division Of Undergraduate Education'}}
|
{'SignBlockName': 'Virginia Carter', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924651'}
|
The 2022 CHIPS & Science Act set in motion a $52B investment in the U.S. domestic semiconductor industry. These investments target the breadth of U.S. semiconductor manufacturing from legacy chip fabrication facilities (fab) to cutting edge silicon integrated circuit (IC) fabs for advanced memory, AI, and quantum computing. The Semiconductor Industry Association (SIA) has estimated that CHIPS projects will add 42,000 fab manufacturing jobs, with additional jobs created in IC equipment, materials, and facilities support companies. Coupled with the downstream labor impact, the total estimated job growth in the U.S. economy from CHIPS investments alone is likely to reach 280,000, and fully half of the IC manufacturing workforce resides in the technician space, populated primarily by associate degree holders. This project will support a novel education alliance centered on multi-modal immersive experiential learning at a leading-edge semiconductor facility, including faculty technical development, based on direct and sustained engagement with IC fab professionals. The alliance incorporates a semiconductor workforce readiness initiative led by a core group of community colleges to adaptively integrate student immersive experiential learning (IEL) with community college degree and certificate programs to promote the education of the skilled technical worker and their transition into the U.S. semiconductor workforce. <br/><br/>The Educational Alliance for Semiconductor Experiential Learning (EASEL) will be initially comprised of NY CREATES (an organization of the Research Foundation of the State University of New York and the SUNY Center for Economic Development) and a core team of four community colleges: Columbus State Community College (CSCC), Onondaga Community College (OCC), LaGuardia Community College (LGCC), and Madison Area Technical College (MATC). NY CREATES operates the only non-commercial 300mm silicon wafer IC fabrication facility in North America and is supported by a team of more than 750 professional semiconductor engineers, technicians, and facilities staff across a 1.65 million square-foot complex that includes 152,000 square-feet of cleanrooms. The complex, an ideal location that has long hosted community college student IEL, maintains a complete IC process flow down to the 5-7 nm device node. It hosts more than 1,000 industry employees. EASEL also includes leading U.S. chip manufacturers, the NSF MNT-EC center, and 9 additional community colleges in key IC manufacturing regions across the U.S. Over the proposed 4-year project it is anticipated that up to 660 student learners and faculty participants will be supported onsite at NY CREATES Albany Nanotech Complex resulting in as much as 43,000 hours of student immersive experiential learning and 4,000 hours of faculty technical development. This project is funded by the Advanced Technological Education program that focuses on the education of technicians for the advanced-technology fields that drive the nation's economy.<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
|
47.076
|
1
|
4900
|
4900
|
2433856
|
[{'FirstName': 'Yves', 'LastName': 'Ngabonziza', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yves Ngabonziza', 'EmailAddress': '[email protected]', 'NSF_ID': '000809993', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Gino', 'LastName': 'Duca', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Gino Duca', 'EmailAddress': '[email protected]', 'NSF_ID': '000960392', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Robert', 'LastName': 'Geer', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robert E Geer', 'EmailAddress': '[email protected]', 'NSF_ID': '000279467', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Michell', 'LastName': 'Ward', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michell A Ward', 'EmailAddress': '[email protected]', 'NSF_ID': '000933889', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Grant', 'LastName': 'Emmel', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Grant R Emmel', 'EmailAddress': '[email protected]', 'NSF_ID': '000940553', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'SUNY Polytechnic Institute', 'CityName': 'ALBANY', 'ZipCode': '122033613', 'PhoneNumber': '5184378689', 'StreetAddress': '257 FULLER RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '20', 'CONGRESS_DISTRICT_ORG': 'NY20', 'ORG_UEI_NUM': 'CDAQNZCL6287', 'ORG_LGL_BUS_NAME': 'THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'SUNY Polytechnic Institute', 'CityName': 'ALBANY', 'StateCode': 'NY', 'ZipCode': '122033640', 'StreetAddress': '257 Fuller Road', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '20', 'CONGRESS_DISTRICT_PERF': 'NY20'}
|
{'Code': '741200', 'Text': 'Advanced Tech Education Prog'}
|
2024~4697075
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433856.xml'}
|
Conference: 1st SIAM Northern and Central California Sectional Conference
|
NSF
|
09/01/2024
|
08/31/2025
| 40,000 | 40,000 |
{'Value': 'Standard Grant'}
|
{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
|
{'SignBlockName': 'Hailiang Liu', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032922436'}
|
The Society for Industrial and Applied Mathematics (SIAM) recently recognized the establishment of the Northern and Central California (SIAM-NCC) Section, whose primary goal is to provide an ongoing opportunity for mathematicians working in the sectors of academia, national laboratory, industry, and government to come together and form a strong social and professional network. The first SIAM-NCC conference scheduled to be held at the University of California, Merced campus during October 9-11, 2024 has the following aims: (1) create an opportunity for scientific researchers in the central and northern California regions to meet, network, and share the innovations and recent developments in their fields; (2) attract and energize a diverse group of students and researchers particularly those from underrepresented minority groups; (3) offer opportunities to SIAM members from various institutions in the region to present their work, who for various reasons often struggle to participate at national and international SIAM meetings; and (4) provide early career researchers to connect with others who are at similar career stages. The broader goal of this conference is to bring together a diverse group of students and researchers particularly those from underrepresented minority groups and create opportunities for sharing ideas and networking. The central and northern California regions provide rich opportunities for involving students from underrepresented and financially challenged populations majoring in science, technology, engineering, and mathematics (STEM) fields.<br/> <br/>The 2024 SIAM-NCC Conference is centered around the following five research themes of applied mathematics: (1) mathematical and numerical analysis; (2) optimization, inverse problems, and optimal experimental design; (3) scientific and high-performance computing; (4) uncertainty quantification and prediction; and (5) scientific machine learning (ML), artificial intelligence (AI), and digital twins. The conference will feature four plenary speakers from industry, academia, and national laboratory. Ten mini-symposia are planned to capture the conference themes in critical areas of research in applied mathematics. Four panels will cover a variety of topics aimed to reach undergraduate and graduate students, early career researchers, and the greater scientific community. In particular, topics include (1) career opportunities for undergraduate students, (2) transitioning from student to researcher (e.g., preparing for internships and postdoc positions), (3) industry and laboratory careers, and (4) the role of AI/ML in science and technology. Finally, to facilitate a more open and informal discussion about research and career opportunities, to accommodate broader research themes, and to offer opportunity for all attendees to present their work, two poster sessions are also scheduled. Undergraduate and graduate students, as well as postdoctoral scholars and other early career researchers, will be particularly encouraged to participate in these sessions. The conference website is: https://sites.google.com/view/siam-ncc/siam-ncc-conference-2024.<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
|
47.049
|
1
|
4900
|
4900
|
2433859
|
[{'FirstName': 'Boaz', 'LastName': 'Ilan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Boaz Ilan', 'EmailAddress': '[email protected]', 'NSF_ID': '000493689', 'StartDate': '07/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Roummel', 'LastName': 'Marcia', 'PI_MID_INIT': 'F', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Roummel F Marcia', 'EmailAddress': '[email protected]', 'NSF_ID': '000083512', 'StartDate': '07/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Noemi', 'LastName': 'Petra', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Noemi Petra', 'EmailAddress': '[email protected]', 'NSF_ID': '000698730', 'StartDate': '07/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Changho', 'LastName': 'Kim', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Changho Kim', 'EmailAddress': '[email protected]', 'NSF_ID': '000789740', 'StartDate': '07/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Erica', 'LastName': 'Rutter', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Erica M Rutter', 'EmailAddress': '[email protected]', 'NSF_ID': '000845780', 'StartDate': '07/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of California - Merced', 'CityName': 'MERCED', 'ZipCode': '953435001', 'PhoneNumber': '2092012039', 'StreetAddress': '5200 N LAKE RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'CA13', 'ORG_UEI_NUM': 'FFM7VPAG8P92', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, MERCED', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California - Merced', 'CityName': 'MERCED', 'StateCode': 'CA', 'ZipCode': '953435001', 'StreetAddress': '5200 N LAKE RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_PERF': 'CA13'}
|
[{'Code': '126600', 'Text': 'APPLIED MATHEMATICS'}, {'Code': '127100', 'Text': 'COMPUTATIONAL MATHEMATICS'}]
|
2024~40000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433859.xml'}
|
SYMPOSIUM: 11th International Brain-Computer Interface Meeting
|
NSF
|
09/01/2024
|
08/31/2025
| 29,941 | 29,941 |
{'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': 'Ephraim Glinert', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924341'}
|
Brain-computer interface (BCI) research explores avenues of controlling devices directly from brain signals. Thus, BCI technology is a powerful control option for neuro-prosthetic limbs, as well as a potential communication option for people with severe motor disabilities or disorders such as amyotrophic lateral sclerosis (ALS), brain stem stroke, cerebral palsy, and spinal cord injury, who may have little or even no muscle control and therefore no means of communication with the external world. The International Brain-Computer Interface (IBCI) meeting is the flagship conference for the field, and the 11th in the series will be held June 2-5, 2025, at the Banff Centre for Arts and Creativity in Alberta, Canada. Effective BCI research requires interdisciplinary interactions involving neuroscience, psychology, engineering, mathematics, computer science, and clinical rehabilitation, and the IBCI meetings serve as critical catalysts for technology dissemination, new collaborations, and educational opportunities for students. Sponsored in the early years primarily by NIH, the IBCI conferences are now under the auspices of the BCI Society, and the 2025 International BCI meeting will focus on emerging applications and techniques to foster research leading to technologies that enable people to interact with the world through brain signals. NSF funding will enable an additional 18 students, including undergraduate and graduate students and postdoctoral fellows, all from United States institutions, to attend and participate in the conference by supporting their travel and registration as well as the cost of student-only events. Student participation in previous IBCI meetings has been very fruitful; many of those students have now graduated and are prominent researchers in the BCI field. The organizers are actively working to recruit student attendees from traditionally underrepresented groups. More information about the conference may be found online at https://bcisociety.org/bci-meeting/. <br/><br/>Reflecting the growth of the field of BCI research, 450 or more participants are expected to attend this year's meeting, including investigators from at least 200 BCI research groups. the program will be similar to that of the successful 2023 meeting, preserving new sessions related to neuroethics and recognition of an exceptional early career researcher. All attendees commit to the entire meeting, from the opening reception and dinner on the evening of Monday, June 2 through the closing session on Thursday afternoon, June 5. A main objective of the conference is to give students a significant educational and professional experience in the BCI field, and to provide opportunities for them to gain depth in their specific interest areas. To these ends, and guided by feedback from a survey of 2018 IBCI attendees, the conference will include interactive events such as workshops and poster sessions along with 7 plenary keynote talks which will be complemented by research sessions and master classes, a BCI users forum as well as BCI didactics sessions, and a Women in BCI social. With all participants housed on site and all meals for all attendees taken together on site, there will be ample opportunity for informal discussions. This creates a unique opportunity for students and trainees to mingle with and learn from established researchers.<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.
|
07/03/2024
|
07/03/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2433860
|
{'FirstName': 'Charles', 'LastName': 'Anderson', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Charles W Anderson', 'EmailAddress': '[email protected]', 'NSF_ID': '000403856', 'StartDate': '07/03/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Colorado State University', 'CityName': 'FORT COLLINS', 'ZipCode': '805212807', 'PhoneNumber': '9704916355', 'StreetAddress': '601 S HOWES ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Colorado', 'StateCode': 'CO', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'CO02', 'ORG_UEI_NUM': 'LT9CXX8L19G1', 'ORG_LGL_BUS_NAME': 'COLORADO STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Banff Centre for Arts and Creatiity', 'CityName': 'Banff, AB', 'StateCode': None, 'ZipCode': 'T1L1H5', 'StreetAddress': '107 Tunnel Mountain Drive', 'CountryCode': 'CA', 'CountryName': 'Canada', 'StateName': 'RI REQUIRED', 'CountryFlag': '0', 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
|
{'Code': '736700', 'Text': 'HCC-Human-Centered Computing'}
|
2024~29941
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433860.xml'}
|
Agile Signal Alignment for Congested and Contested Spectrum Access
|
NSF
|
01/01/2025
|
12/31/2027
| 399,947 | 399,947 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Huaiyu Dai', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924568'}
|
As we begin to explore novel paradigms for next-generation spectrum access and management, there is growing consensus that non-exclusive spectrum sharing strategies will play a key role in realizing a compelling vision for Spectrum Era 4. Every non-exclusive use system is subject to unintended and unpredictable interference; even exclusive-use systems can suffer from interference due to misbehaving or malicious agents. Finding more effective ways to deal with interference is of paramount importance on the road towards Spectrum Era 4 wireless prominence, which is needed to sustain the US technological and intellectual leadership and to support a thriving US economy. This project will develop a fundamentally new paradigm for efficient and reliable communication in the presence of unpredictable interference. It will improve the performance, resilience, and reliability of wireless systems operating in shared, congested, and contested spectrum bands. The project specifically aims to address mitigation and autonomous recovery from harmful interference, service degradation or denial – key new spectrum capabilities that will empower Spectrum Era 4 systems. The research draws from wireless communications theory and practice (including software radio programming and experimentation), statistical machine learning, signal processing and linear algebra. The findings will make impactful contributions to shared-spectrum wireless communications by introducing novel interference-immune communication modalities, with broader impacts on the above constituent disciplines. The project will offer exciting educational opportunities and added value in terms of spectrum workforce development. Communications engineers with solid theoretical training and hands-on software radio skills are highly sought-after in Northern Virginia and other wireless industry hubs around the US. As part of this project, the PI will also work to identify and motivate underrepresented students for undergraduate research, and to support his department’s broadening participation plan through the Allyship program that he helped co-found in 2020.<br/><br/>The PI recently proposed a very simple and practical method for (re)using spectrum occupied by a legacy service (e.g., analog or digital broadcast). The idea is to use repetition coding in a way that induces a common 1-D signal subspace at the multi-antenna receiver, while interference is different and spans distinct subspaces. Thus the signal of interest can be uniquely recovered using subspace intersection, implemented via canonical correlation analysis (CCA). This signal alignment approach has been demonstrated to work under adverse time-varying interference, without any coordination or channel state information. Signal alignment is well-positioned to address key Spectrum Era 4 challenges, including autonomous recovery from service degradation, denial of service, security and privacy concerns. The project is designed to leverage signal alignment for effective communication in congested and contested environments, with particular focus on the following synergistic thrusts: 1) Streaming Time-Frequency Signal Alignment: Leveraging the algebraic structure of CCA and the shift structure of streaming data to enable computationally lightweight time-frequency signal alignment under unpredictable (e.g., intermittent) and potentially harmful interference; 2) Signal Alignment for Ultra Reliable Low Latency Communications (URLLC): Building on surprising insights obtained recently by the PI to boost CCA performance in the sample-starved (short packet) regime; 3) Full-rate Signal Alignment: Avoiding repetition which halves the transmission rate, this thrust will design and study the performance of signal alignment strategies that operate close to full-rate; and 4) Software radio experiments and validation: Judicious experiments will be conducted at UVA and the COSMOS PAWR testbed at Rutgers/WINLAB to validate the research in 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.
|
08/19/2024
|
08/19/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2433870
|
{'FirstName': 'Nikolaos', 'LastName': 'Sidiropoulos', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nikolaos D Sidiropoulos', 'EmailAddress': '[email protected]', 'NSF_ID': '000228544', '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': '140Y00', 'Text': 'SWIFT-Spectrum Innov Futr Tech'}
|
2024~399947
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433870.xml'}
|
I-Corps: Translation Potential of an Intracranial Device to Treat Neurodegenerative Disease
|
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': 'Molly Wasko', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924749'}
|
The broader impact of this I-Corps project is based on the development of an intracranial device to treat neurodegenerative disease, such as Alzheimer’s or Parkinson’s. Current treatment devices involve helmets or headwear, and stigma around these bulky devices affects patient self-esteem and deters patient usage. This technology aims to be mostly intracranial (with the potential exception of small, flush hardware extracranially), and thus, may be associated with better patient satisfaction and well-being. Furthermore, given the estimated $655 billion spent yearly on neurodegenerative diseases in the United States, this technology has potential for financial impact if successful in slowing progression or alleviating symptoms of neurodegenerative diseases. <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. The solution is based on the development of an intracranial device that works through cellular photobiomodulation (PBM) to treat neurodegenerative diseases, such as Alzheimer’s or Parkinson’s. This approach creates minimally invasive burr holes over affected regions of the brain, which would be closed with a direct targeting photobiomodulation device to apply the therapy uncompromised by attenuating obstructions. For example, PBM holds promise as a postsurgical healing tool, especially in surgeries that require burr holes, by eliminating the need to penetrate additional tissue to reach clinically relevant structures. This device could deliver therapeutic benefit for certain neurological afflictions and could contribute to a better understanding of the mechanisms of PBM therapy that may inform targets for novel therapies.<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.
|
07/01/2024
|
07/01/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2433881
|
{'FirstName': 'Shahram', 'LastName': 'Majidi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shahram Majidi', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A0B12', 'StartDate': '07/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Icahn School of Medicine at Mount Sinai', 'CityName': 'NEW YORK', 'ZipCode': '100296504', 'PhoneNumber': '2128248300', 'StreetAddress': '1 GUSTAVE L LEVY PL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'NY13', 'ORG_UEI_NUM': 'C8H9CNG1VBD9', 'ORG_LGL_BUS_NAME': 'ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI', 'ORG_PRNT_UEI_NUM': 'C8H9CNG1VBD9'}
|
{'Name': 'Icahn School of Medicine at Mount Sinai', 'CityName': 'NEW YORK', 'StateCode': 'NY', 'ZipCode': '100296504', 'StreetAddress': '1 GUSTAVE L LEVY PL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_PERF': 'NY13'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433881.xml'}
|
CAREER: Past, Present, and Future of the Peatlands of the Caribbean: Implications for the Carbon Cycle in a Changing Climate
|
NSF
|
01/01/2024
|
05/31/2027
| 816,374 | 641,031 |
{'Value': 'Continuing Grant'}
|
{'Code': '08010000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'DEB', 'LongName': 'Division Of Environmental Biology'}}
|
{'SignBlockName': 'Matthew Kane', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927186'}
|
Tropical ecosystems are subject to some of the highest rates of land-use change and degradation globally. These ecosystems are also being affected by climate variability and warming. Changes in land-use have the potential for important feedbacks on our climate, especially via the carbon cycle. However, the magnitude of these feedbacks on ecosystems are uncertain. This is particularly the case for soil carbon in the tropics. Field measurements of the extent and location of carbon stored in tropical soils, and the processes that control net carbon balance remain sparse. This study specifically looks at tropical peatlands, a very carbon-rich type of habitat. Current maps are believed to significantly underestimate tropical wetland (and peatland) areas resulting in unreliable carbon stock estimates. Likewise, the origin, timing, and developmental history of peatland complexes across the tropics are poorly known, making it challenging to identify and quantify the main controls on peat formation. These data and knowledge gaps make it difficult to predict peatland evolution and their associated carbon content under present and future conditions. As such, ecologists don’t quite understand where or why peat forms under tropical conditions, and what controls accumulation rates. This project is the first to aim at gaining an integrated understanding of the origin and development of Caribbean peatlands, and will use extensive field surveys, detailed peat-core data and synthesis, as well as process-based computer modeling. This CAREER project will contribute to the US world-leading expertise in Earth System Science, advance the peatland community’s research needs, and guide policy and land management decisions.<br/><br/>This research project combines new field work with paleoecological and modeling studies as well as extensive student training on the terrestrial carbon balance of Caribbean peatlands. The PI and her team will be integrating 1) new data collection from multiple sites along the Caribbean coast of Nicaragua and Costa Rica, 2) a synthesis of existing data from other Caribbean peatlands, and 3) processed-based ecological simulations. The overarching question this project addresses is: what are the conditions that enable peatland initiation, facilitate peat development, and control peatland C balance over decadal to millennial timescales? The existence of peat deposits across the study region will be mapped and confirmed using extensive field surveys. How and when Caribbean peatlands became established will be determined by using detailed peat-core data and synthesis of published records. C stocks will be estimated, and the relationships between the rate of peat formation and paleoenvironmental change will be examined. Using process-based peatland models, C sequestration rates will be simulated and quantified to elucidate the current function of Carribean peatlands, and forecast how they might respond to natural and anthropogenic forcings in the future. Overall, this project will produce the first comprehensive assessment of the location, extent, genesis, and development of Caribbean peatlands. This work is necessary to assess the past, present, and future resilience of tropical ecosystems and to help inform land management decisions; it will also allow ecologists to benchmark Earth System Models and test hypotheses about the role of tropical peatlands in the Holocene global C cycle.<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
|
47.074
|
1
|
4900
|
4900
|
2433890
|
{'FirstName': 'Julie', 'LastName': 'Loisel', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Julie Loisel', 'EmailAddress': '[email protected]', 'NSF_ID': '000581812', 'StartDate': '05/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Board of Regents, NSHE, obo University of Nevada, Reno', 'CityName': 'RENO', 'ZipCode': '895570001', 'PhoneNumber': '7757844040', 'StreetAddress': '1664 N VIRGINIA ST # 285', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Nevada', 'StateCode': 'NV', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'NV02', 'ORG_UEI_NUM': 'WLDGTNCFFJZ3', 'ORG_LGL_BUS_NAME': 'BOARD OF REGENTS OF THE NEVADA SYSTEM OF HIGHER ED', 'ORG_PRNT_UEI_NUM': 'WLDGTNCFFJZ3'}
|
{'Name': 'Board of Regents, NSHE, obo University of Nevada, Reno', 'CityName': 'RENO', 'StateCode': 'NV', 'ZipCode': '895570001', 'StreetAddress': '1664 N VIRGINIA ST # 285', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Nevada', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'NV02'}
|
{'Code': '738100', 'Text': 'Ecosystem Science'}
|
2023~641031
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433890.xml'}
|
I-Corps: Translation Potential of a Deep Eutectic Solvent Technology for Critical Metal Recovery from Expired Batteries
|
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': 'Molly Wasko', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924749'}
|
The broader impact of this I-Corps project is based on the development of a sustainable method for recycling expired lithium-ion batteries. This advance represents a significant improvement over current recycling methods, offering a more effective and environmentally friendly solution, crucial for sustainable resource management. This technology employs green solvents that reduce hazardous waste and resource consumption, emphasizing resource efficiency and minimizing ecological impact. Additionally, this technology enhances public health and safety by cutting down the use of dangerous chemicals in the recycling process, thereby reducing health risks to workers and preventing environmental contamination. Overall, this lithium-ion battery recycling technology meets critical industry needs while also serving broader societal objectives, fostering a healthier, safer, and more sustainable future for all.<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. The solution is based on the development of a deep eutectic solvent (DES)-based technology for recycling critical metals from expired lithium-ion batteries. This innovative technology efficiently recovers critical metals, such as lithium, cobalt, nickel, and manganese, with high purity and selectivity. By selectively extracting and recycling these critical metals, this technology can reduce environmental impact and promote a circular economy. In addition, this technology uses a solvent that can be derived from low-cost plant materials and is recyclable, which means low cost and minimal wastewater generation. This solution also operates under mild reaction conditions, so it has fewer safety concerns and environmental hazards. This advance represents a significant improvement over current recycling methods, offering a more effective, efficient, and environmentally friendly solution for critical metal recovery from lithium-ion batteries.<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.
|
07/23/2024
|
07/23/2024
|
None
|
Grant
|
47.084
|
1
|
4900
|
4900
|
2433893
|
{'FirstName': 'Jian', 'LastName': 'Shi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jian Shi', 'EmailAddress': '[email protected]', 'NSF_ID': '000724094', 'StartDate': '07/23/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Kentucky Research Foundation', 'CityName': 'LEXINGTON', 'ZipCode': '405260001', 'PhoneNumber': '8592579420', 'StreetAddress': '500 S LIMESTONE', 'StreetAddress2': '109 KINKEAD HALL', 'CountryName': 'United States', 'StateName': 'Kentucky', 'StateCode': 'KY', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'KY06', 'ORG_UEI_NUM': 'H1HYA8Z1NTM5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF KENTUCKY RESEARCH FOUNDATION, THE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Kentucky Research Foundation', 'CityName': 'LEXINGTON', 'StateCode': 'KY', 'ZipCode': '405260001', 'StreetAddress': '500 S LIMESTONE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Kentucky', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'KY06'}
|
{'Code': '802300', 'Text': 'I-Corps'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433893.xml'}
|
CUE-P: Artificial Intelligence Entry Pathways
|
NSF
|
01/01/2025
|
12/31/2027
| 1,999,953 | 1,940,249 |
{'Value': 'Continuing Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Allyson Kennedy', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032928905'}
|
This Computing in Undergraduate Education (CUE) Pathways project is a partnership led by Miami Dade College, Houston Community College, and Maricopa County Community College District, in collaboration with a network of school districts and industry partners. The goal of this collaboration is to improve underrepresented students’ entry access to artificial intelligence (AI) degrees from community colleges by developing scalable strategies that support high school students and adult learners. The project will establish entry pathways into AI education and best practices on how to recruit, retain, complete and transition underrepresented students in AI programs. The broader impacts of the project include the dissemination and adaptation of pedagogical practices, strategic initiatives, and academic entry pathways with other institutions of education committed to advancing knowledge and implementing practical applications to broaden participation of underrepresented students in AI fields of study. Pedagogical expertise and college program preparation frameworks for the emerging and rapidly changing AI workforce is replicable and sustainable at other institutions working with underrepresented populations including high school students and adult learners.<br/><br/>The goal of this CUE Pathways project will be accomplished through the following objectives: (1) to develop and disseminate an AI Framework for high school students to be adequately engaged and prepared for a two-year AI degree program at a community college.; (2) to develop and implement an AI Teacher Academy to train high school teachers on properly preparing underrepresented students for educational pathways and careers in AI; (3) to adequately engage underrepresented and underserved high school students in academic AI-related activities including camps and dual enrollment courses as an entry pathway to community college AI degree programs; and (4) to implement strategies to support underrepresented and underserved adult learners joining two-year AI programs at community colleges. This goal and objectives will be met via the following activities: high school AI Framework development and dissemination; AI Teacher Academy development and implementation; camps; dual enrollment; AI Readiness training; and faculty professional 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.
|
08/26/2024
|
08/26/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2433939
|
[{'FirstName': 'Samir', 'LastName': 'Saber', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Samir Saber', 'EmailAddress': '[email protected]', 'NSF_ID': '000705939', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Antonio', 'LastName': 'Delgado', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Antonio Delgado', 'EmailAddress': '[email protected]', 'NSF_ID': '000756193', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Habib', 'LastName': 'Matar', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Habib Matar', 'EmailAddress': '[email protected]', 'NSF_ID': '000838436', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Nickolas', 'LastName': 'Dodd', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nickolas Dodd', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A08RM', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Miami Dade College', 'CityName': 'MIAMI', 'ZipCode': '331322206', 'PhoneNumber': '3052373910', 'StreetAddress': '245 NE 4TH ST BLDG 3000', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '27', 'CONGRESS_DISTRICT_ORG': 'FL27', 'ORG_UEI_NUM': 'SJ72FRUKYQH4', 'ORG_LGL_BUS_NAME': 'MIAMI-DADE COLLEGE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Miami Dade College', 'CityName': 'Miami', 'StateCode': 'FL', 'ZipCode': '331322204', 'StreetAddress': '300 N.E. 2nd Avenue', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '27', 'CONGRESS_DISTRICT_PERF': 'FL27'}
|
[{'Code': '134Y00', 'Text': 'CSforAll-Computer Sci for All'}, {'Code': '279Y00', 'Text': 'IUSE: Computing Undergrad Educ'}, {'Code': '296Y00', 'Text': 'NAIRR-Nat AI Research Resource'}]
|
2024~1940249
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433939.xml'}
|
Demystifying the Academic Tenure Pathway for Early Career Scientists
|
NSF
|
08/01/2024
|
07/31/2025
| 23,476 | 23,476 |
{'Value': 'Standard Grant'}
|
{'Code': '06040100', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'OCE', 'LongName': 'Division Of Ocean Sciences'}}
|
{'SignBlockName': 'Elizabeth Rom', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032927709'}
|
Early Career Scientists (ECS), including undergraduates through pre-tenured faculty, often lack knowledge about the tenure pathway in academia. This lack of knowledge about the process of obtaining a tenure job carries through all stages of ECSs in different ways. Undergraduate students, particularly first-generation students, do not have opportunities to learn about this process in any curricula unless they have a mentor helping them and educating them at each step of the way. Topics that are important at this stage include internships and cultivating a resume that speaks to your interests, types of academic jobs, research opportunities, and the graduate application process. Graduate students are not given opportunities to practice communication skills, which are pivotal at this stage as students begin to start networking for post-doctoral positions or teaching positions. Post-doctoral candidates lack opportunities for gaining interview skills. Finally, once the tenure-track position has been obtained, assistant professors are expected to know how to create a dossier and how they are evaluated for tenure. They may also attempt to maintain work-life balance. This award supports a workshop that will address the issues facing ECS as they navigate pathways towards academic careers. The workshop will be run during the 2025 Association for the Sciences of Limnology and Oceanography (ASLO) meeting in Charlotte, North Carolina. The organizers expect that workshop participants will gain knowledge about each stage of the academic career process from undergraduate through pre-tenured faculty, and they will benefit from professional development during the conference when they may be able to put the knowledge gained to immediate use.<br/><br/>The PI proposes a workshop that will have an important outcome of engaging early career ocean scientists in discussions of how to navigate academic careers. The effort will support ECS, particularly those who are from underrepresented groups or who are first-generation students. In addition, Dr. Schiebel will mentor two undergraduate students from Suffolk University who will be taking part in the workshop, presenting their research at the ASLO meeting, and attending their first scientific conference.<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.
|
07/08/2024
|
07/08/2024
|
None
|
Grant
|
47.050
|
1
|
4900
|
4900
|
2433961
|
{'FirstName': 'Hayley', 'LastName': 'Schiebel', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hayley Schiebel', 'EmailAddress': '[email protected]', 'NSF_ID': '000715557', 'StartDate': '07/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Suffolk University', 'CityName': 'BOSTON', 'ZipCode': '021083916', 'PhoneNumber': '6175738400', 'StreetAddress': '73 TREMONT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_ORG': 'MA08', 'ORG_UEI_NUM': 'EYKDJZZMDGA7', 'ORG_LGL_BUS_NAME': 'SUFFOLK UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Suffolk University', 'CityName': 'BOSTON', 'StateCode': 'MA', 'ZipCode': '021083916', 'StreetAddress': '73 TREMONT ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_PERF': 'MA08'}
|
{'Code': '169000', 'Text': 'EDUCATION/HUMAN RESOURCES,OCE'}
|
2024~23476
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433961.xml'}
|
Collaborative Research: NewSpectrum: Track 1: Distributed Data-Driven Spectrum Management Architecture for the Next Era of Wireless
|
NSF
|
10/01/2024
|
09/30/2027
| 249,430 | 249,430 |
{'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'}
|
Wireless communication services and associated applications rely on the use of radio frequency (RF) spectrum resources for their operation. Due to the rapid growth in the use of these services, spectrum management agencies and wireless service providers need to migrate from current spectrum use practices to more dynamic spectrum assignment and sharing mechanisms. This project addresses these challenges by focusing on the design and validation of a distributed and data-driven next-generation architecture for dynamic spectrum management among decentralized and heterogeneous wireless systems. Aspects of the distributed spectrum architecture are expected to influence future technical standards. The outcomes of the project will be made available to the wireless/networking industry through mechanisms such as the bi-annual WINLAB industrial advisory meeting. The project integrates activities related to the use and design of spectrum deconfliction protocols and the execution of measurements to design and use spectrum consumption models into the annual WINLAB summer internship program which involves about 30 to 40 undergraduate students each year.<br/><br/>Distributed dynamic spectrum management aims to overcome the limitations of centralized control such as limited scalability and single point of failure, while still achieving high levels of spectrum efficiency. The distributed data-driven spectrum management (D3SM) architecture that serves as the baseline for this project uses an Internet-based control plane that facilitates the operation of dynamic spectrum sharing algorithms between peer networks. This control plane for spectrum coordination supports the exchange of and processing of fine-grained meta-data about the local wireless environment in the form of standardized radio frequency spectrum usage descriptors known as “spectrum consumption models (SCMs)” which have recently been standardized. Such spectrum usage data can be used to realize a flexible range of distributed algorithms and dynamic interactions for spectrum coordination. It is noted that a suitably designed distributed spectrum management framework can also accommodate some level of hierarchically organized centralized coordination where appropriate. The project is based on a multi-stage evaluation methodology that starts with architectural design of D3SM with the required protocols and algorithms, followed by simulation and indoor testbed emulation of a number of use case scenarios including spectrum sharing between cellular operators, coexistence of WiFi and 5G, and interference management for passive wireless devices such as those used for weather forecasting and radio astronomy. These studies are expected to lead to an experimentally validated set of protocols and algorithms for distributed and partially centralized spectrum management methods.<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.
|
08/22/2024
|
08/22/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2433974
|
{'FirstName': 'Carlos', 'LastName': 'Caicedo Bastidas', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Carlos E Caicedo Bastidas', 'EmailAddress': '[email protected]', 'NSF_ID': '000554328', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Syracuse University', 'CityName': 'SYRACUSE', 'ZipCode': '13244', 'PhoneNumber': '3154432807', 'StreetAddress': '900 S CROUSE AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '22', 'CONGRESS_DISTRICT_ORG': 'NY22', 'ORG_UEI_NUM': 'C4BXLBC11LC6', 'ORG_LGL_BUS_NAME': 'SYRACUSE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Syracuse University', 'CityName': 'SYRACUSE', 'StateCode': 'NY', 'ZipCode': '132444407', 'StreetAddress': '900 S CROUSE AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '22', 'CONGRESS_DISTRICT_PERF': 'NY22'}
|
{'Code': '140Y00', 'Text': 'SWIFT-Spectrum Innov Futr Tech'}
|
2024~249430
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433974.xml'}
|
Collaborative Research: NewSpectrum: Track 1: Distributed Data-Driven Spectrum Management Architecture for the Next Era of Wireless
|
NSF
|
10/01/2024
|
09/30/2027
| 550,000 | 550,000 |
{'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': 'Alhussein Abouzeid', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032920000'}
|
Wireless communication services and associated applications rely on the use of radio frequency (RF) spectrum resources for their operation. Due to the rapid growth in the use of these services, spectrum management agencies and wireless service providers need to migrate from current spectrum use practices to more dynamic spectrum assignment and sharing mechanisms. This project addresses these challenges by focusing on the design and validation of a distributed and data-driven next-generation architecture for dynamic spectrum management among decentralized and heterogeneous wireless systems. Aspects of the distributed spectrum architecture are expected to influence future technical standards. The outcomes of the project will be made available to the wireless/networking industry through mechanisms such as the bi-annual WINLAB industrial advisory meeting. The project integrates activities related to the use and design of spectrum deconfliction protocols and the execution of measurements to design and use spectrum consumption models into the annual WINLAB summer internship program which involves about 30 to 40 undergraduate students each year.<br/><br/>Distributed dynamic spectrum management aims to overcome the limitations of centralized control such as limited scalability and single point of failure, while still achieving high levels of spectrum efficiency. The distributed data-driven spectrum management (D3SM) architecture that serves as the baseline for this project uses an Internet-based control plane that facilitates the operation of dynamic spectrum sharing algorithms between peer networks. This control plane for spectrum coordination supports the exchange of and processing of fine-grained meta-data about the local wireless environment in the form of standardized radio frequency spectrum usage descriptors known as “spectrum consumption models (SCMs)” which have recently been standardized. Such spectrum usage data can be used to realize a flexible range of distributed algorithms and dynamic interactions for spectrum coordination. It is noted that a suitably designed distributed spectrum management framework can also accommodate some level of hierarchically organized centralized coordination where appropriate. The project is based on a multi-stage evaluation methodology that starts with architectural design of D3SM with the required protocols and algorithms, followed by simulation and indoor testbed emulation of a number of use case scenarios including spectrum sharing between cellular operators, coexistence of WiFi and 5G, and interference management for passive wireless devices such as those used for weather forecasting and radio astronomy. These studies are expected to lead to an experimentally validated set of protocols and algorithms for distributed and partially centralized spectrum management methods.<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.
|
08/22/2024
|
08/22/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2433975
|
[{'FirstName': 'Dipankar', 'LastName': 'Raychaudhuri', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dipankar Raychaudhuri', 'EmailAddress': '[email protected]', 'NSF_ID': '000181288', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Ivan', 'LastName': 'Seskar', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ivan Seskar', 'EmailAddress': '[email protected]', 'NSF_ID': '000195782', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Rutgers University New Brunswick', 'CityName': 'NEW BRUNSWICK', 'ZipCode': '089018559', 'PhoneNumber': '8489320150', 'StreetAddress': '3 RUTGERS PLZ', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NJ12', 'ORG_UEI_NUM': 'M1LVPE5GLSD9', 'ORG_LGL_BUS_NAME': 'RUTGERS, THE STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Rutgers University New Brunswick', 'CityName': 'NEW BRUNSWICK', 'StateCode': 'NJ', 'ZipCode': '089018559', 'StreetAddress': '3 RUTGERS PLZ', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'NJ12'}
|
{'Code': '140Y00', 'Text': 'SWIFT-Spectrum Innov Futr Tech'}
|
2024~550000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433975.xml'}
|
Track 1: EFFICIENT: BackscattEr Fabric For MultidImensional SpeCtrum SItuational AwarENess and ProTection
|
NSF
|
01/01/2025
|
12/31/2027
| 800,000 | 800,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Huaiyu Dai', 'PO_EMAI': '[email protected]', 'PO_PHON': '7032924568'}
|
The next era of spectrum is envisioned to have spatially and spectrally adjacent systems that are dynamic, resulting in frequent cross-system interference. Naturally, interference lies at the heart of spectrum sharing and involves a network of radio transceivers, distributed in space with varying behavior over time. Mechanisms used in the current and past eras of spectrum management, have all run up against limitations owing to the cost and potential lack of scalability of such solutions. Cost is relevant to hardware complexity of the radio front-end, which, for the case of higher frequencies in the-tens of gigahertz-regime, becomes even more critical. Computational complexity of the proposed algorithms, coordination among the network terminals required for the proposed solutions (and necessary power and bandwidth resources for such coordination), and finally, distributed channel estimation (and the necessary resources to acquire such information) all contribute to the complexity. This project enables affordable, accurate, near-real-time spectrum situational awareness, including simple spectrum sensing algorithms, distributed mechanisms, and relevant spectrum sensing hardware. In addition, this project targets mechanisms at the physical layer that provide some form of radio waveform protection against malicious or unwanted interference, without modifying the core of the existing radio infrastructure. This work puts forth both spectrum situational awareness and protection from interference, exploiting ultra-low complexity radio hardware and non-coherent techniques; the basic idea lies at the heart of backscatter radio, which enables a fabric of low-complexity backscatter tags for said objectives. These tags are controlled through the receiver/gateway, connected to the cloud, without however requiring channel state information (CSI) regarding any of the involved links.<br/><br/>The proposed fabric offers an intelligent, yet low-cost solution with minimal hardware complexity (due to the adopted backscatter radio tags), limited channel state information (due to the proposed non-coherent algorithms), with the capacity to observe signal strength (power), frequencies and direction-of-arrival (DoA) for a set of in-band, simultaneously operating links. Such multidimensional spectrum situational awareness comes with a collateral dividend: interference protection, i.e., the ability to cancel interference at specific receiver locations. Techniques developed include both model-based, as well as data-driven machine learning (ML) approaches. In addition, this work targets demonstration of the proposed principles in the FR3 band, with a particular focus on the 12.2 − 12.7 GHz band, where next generation cellular, digital video broadcasting and low-earth orbit satellite (SAT) radio applications have the potential to coexist. The research will focus on three key thrusts: (1) Thrust 1 develops a framework for multidimensional spectrum situational awareness using a backscatter fabric. (2) Thrust 2 develops a framework for spectrum protection at the PHY layer using non-coherent, data-driven, DoA assisted protection algorithms against interference. (3) Thrust 3 focuses on experimental evaluation on the COSMOS Testbed using the illustrative example of 5G Terrestrial Network and SAT co-existence in FR3 spectrum. The project will also quantify the density and spatial coverage requirements of the backscatter fabric to enable spectrum situational awareness and spectrum protection across a variety of spectrum bands. The creation of the backscatter fabric will lead to the development of robust solutions for spectrum situational awareness and protection, contributing to the envisioned Spectrum Era 4 and the ever-expanding problem of meeting increasing wireless data demands. Furthermore, the project’s theme is well-suited for the development of STEM projects that will captivate students at various educational levels.<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.
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08/19/2024
|
08/19/2024
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None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2433991
|
[{'FirstName': 'Ivan', 'LastName': 'Seskar', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ivan Seskar', 'EmailAddress': '[email protected]', 'NSF_ID': '000195782', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Narayan', 'LastName': 'Mandayam', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Narayan Mandayam', 'EmailAddress': '[email protected]', 'NSF_ID': '000492962', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'AGGELOS', 'LastName': 'BLETSAS', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'AGGELOS BLETSAS', 'EmailAddress': '[email protected]', 'NSF_ID': '0000A05WR', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Rutgers University New Brunswick', 'CityName': 'NEW BRUNSWICK', 'ZipCode': '089018559', 'PhoneNumber': '8489320150', 'StreetAddress': '3 RUTGERS PLZ', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NJ12', 'ORG_UEI_NUM': 'M1LVPE5GLSD9', 'ORG_LGL_BUS_NAME': 'RUTGERS, THE STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Rutgers University New Brunswick', 'CityName': 'NEW BRUNSWICK', 'StateCode': 'NJ', 'ZipCode': '089018559', 'StreetAddress': '3 RUTGERS PLZ', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'NJ12'}
|
{'Code': '140Y00', 'Text': 'SWIFT-Spectrum Innov Futr Tech'}
|
2024~800000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2433991.xml'}
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