Project Grant 2523615
- The National Science Foundation awarded a $350,000 Project Grant to the University of Washington under the Mathematical and Physical Sciences federal grant program (CFDA 47.049) to develop novel strategies for constructing optimal statistical estimators using machine learning tools. Over a three-year period ending August 2025, the investigators will study representations of the efficient influence function that can be computed numerically to derive new asymptotically efficient estimators. They...
- The University of Washington was awarded a $169,769 Project Grant from the National Science Foundation (NSF) under the Mathematical and Physical Sciences program (CFDA 47.049) to support predictive simulations of complex kinetic systems from October 1, 2021 through September 30, 2022. As the prime awardee, the University will utilize the funding to develop computational models and conduct simulations that advance understanding of major problems in mathematical and physical sciences....
- This $199,400 Project Grant award from the National Science Foundation (NSF) under the Mathematical and Physical Sciences program (CFDA 47.049) will fund collaborative research to augment continuous data assimilation and perform equation discovery with applications in geophysics. The research aims to develop more accurate predictive models for complex systems like weather, ocean currents, and groundwater flow by systematically adapting and modifying existing physically derived models using...
- This $347,193 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program will support the University of Washington's research on continuum kinetic studies of hydrodynamic and magnetohydrodynamic instabilities. The project aims to address long-standing discrepancies between high-energy-density experiments and simulations, which could advance the understanding of plasma transport with implications for astrophysics, national...
- The University of Washington will receive $290,678 from the National Science Foundation under a Project Grant award titled "FULLY NONLINEAR ELLIPTIC EQUATIONS." The grant period runs from July 1, 2021 through June 30, 2024. The funding supports the Mathematical and Physical Sciences program (CFDA 47.049), which aims to promote progress in the mathematical and physical sciences to strengthen the Nation's scientific enterprise. Specifically, the University will advance understanding of...
- This $250,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will fund research by the University of Washington to explore the use of machine learning and artificial intelligence algorithms to augment limited datasets and improve statistical inference. The project will take a three-pronged approach: 1) establishing new semi-parametric efficiency results for semi-supervised learning, 2) developing new and improved...
- This $149,999 Project Grant award from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) supports research into techniques for identifying hidden or unknown components in nonlinear differential equation models. The research aims to improve modeling and predictive capabilities for complex physical phenomena, such as fluid flows, turbulence, and weather prediction. The award to the Research Foundation of the City University of New York will provide...
- The National Science Foundation (NSF) awarded a $132,000 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) federal grant program to Brigham Young University (BYU) to develop new methods for accurately modeling and forecasting complex physical systems like weather, ocean currents, and groundwater flow. The project aims to augment existing physics-based models with machine learning techniques to capture physical phenomena more accurately while maintaining scientific...
- The National Science Foundation (NSF) awarded a $108,010 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) program to the University of Washington (UW) for the project "CAREER: Mathematical Aspects of Topological Phases". The 5-year project, running from July 1, 2025 to June 30, 2030, aims to advance the scientific understanding of topological phases of matter and their potential applications in quantum technology. Key objectives include investigating stable...
- The National Science Foundation awarded a $225,000 Project Grant under the Engineering (47.041) federal grant program to the University of Colorado from July 1, 2023 to June 30, 2026. The University will develop a physics-informed real-time optimal power flow model using machine learning techniques to provide close to optimal solutions for power plant outputs while considering dynamic constraints to avoid grid instabilities. Key activities include advancing techniques combining...
The National Science Foundation awarded a $250,012 Project Grant to the University of Washington under the Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049) with a performance period from September 15, 2025 to August 31, 2028. The grant supports the development of machine learning tools for data assimilation and model calibration applicable to a broad range of physical systems described by ordinary, differential algebraic, or partial differential equations. The project aims to expand the toolbox available to scientists and engineers for accurately simulating power grid behavior and predicting the impact of changes to power systems, with potential applications in fields such as atmospheric sciences, oceanography, ecology, and astronomy. The grant supports fundamental research with the goal of producing a novel set of tools that enable proper uncertainty quantification and have rigorous theoretical guarantees for efficient implementation in practical settings.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $250.0k | 8/6/25 |