Project Grant 2608502
- The National Science Foundation Directorate for Mathematical and Physical Sciences awarded $250,000 to the University of Wisconsin – Madison on September 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop high-fidelity generative mean flow models that advance scientific machine learning through a theory-validation feedback loop. The project addresses critical limitations in applying generative AI to physical simulations by building a new class of AI models...
- The National Science Foundation (NSF) awarded a $250,000 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to the University of Utah. The grant, with a performance period from October 1, 2024 to September 30, 2027, will fund collaborative research to develop the theoretical foundations for AI-assisted digital twins to integrate scientific data, physical models, and machine learning for complex high-power laser science and engineering. The project aims to enable...
- The National Science Foundation Division of Materials Research awarded the University of Utah $328,828 on August 15, 2026, for collaborative research developing a motif-based deep learning framework to predict and interpret structural disorder in crystalline solids. The award, supported under the Mathematical and Physical Sciences program (CFDA 47.049), funds research using Zintl phases as a model system to link quantum mechanical simulations, materials databases, and deep learning to uncover...
- The National Science Foundation Directorate for Mathematical and Physical Sciences awarded the University of Washington $139,997 on September 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop mathematical theory and computational tools that explain how randomness in data and algorithms combine to shape the performance of large-scale computational methods. The project will build new theoretical frameworks and practical forecasting approaches for randomized...
- Federal Project Grant Award Summary The University of Utah received a $300,772 Project Grant from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049), awarded July 15, 2025, with completion targeted for June 30, 2028. This collaborative research initiative develops and analyzes computational methods for solving extremal eigenvalue problems with geometric constraints, with applications to physical phenomena...
- Federal Project Grant Award Summary The University of Utah received a $444,202 Project Grant from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049), awarded September 15, 2025, with completion targeted for August 31, 2028. This collaborative research initiative develops computationally efficient hypercomplex variable-based sensitivity methods to accelerate digital twin (DT) model updating processes. The...
- The National Science Foundation Division of Mathematical Sciences awarded $199,000 to the University of Houston System on July 1, 2026, for development of a learning-augmented multiscale modeling framework for flow in porous media, under the Mathematical and Physical Sciences program (CFDA 47.049). The project develops mathematical and computational approaches combining multiscale modeling with machine learning to improve reduced models for complex flow systems in energy and environmental...
- The National Science Foundation (NSF) awarded a $230,111 Project Grant under its Mathematical and Physical Sciences (CFDA 47.049) program to the University of Utah's Office of Sponsored Projects Division. This 3-year grant, effective from July 1, 2024 to June 30, 2027, supports two scientific research threads: (1) fundamental research on liquid crystals, their suspensions, and related applications; and (2) investigations of extreme wave phenomena in photonic devices, with a focus on epsilon near...
- The National Science Foundation Directorate for Mathematical and Physical Sciences awarded the University of Massachusetts $300,000 on August 15, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop mathematical principles that make artificial intelligence systems more stable, reliable, and robust. The project establishes foundational theory to explain why successful AI algorithms work, identify conditions under which they fail, and guide their design for...
- The National Science Foundation Directorate for Mathematical and Physical Sciences awarded the University of Delaware $325,000 on August 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop computational and mathematical modeling frameworks for designing integrated energy microgenerators (IEMGs). The project focuses on simulating optoelectronic devices in IEMGs—miniature energy harvesters capable of powering sensors and actuators embedded in textiles,...
The National Science Foundation Directorate for Mathematical and Physical Sciences awarded the University of Utah $250,000 on September 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop high-fidelity generative mean flow models that integrate artificial intelligence with computational mathematics for scientific machine learning applications. The research addresses computational accuracy and speed challenges in flow-based generative models by establishing a theory-validation feedback loop designed to advance algorithmic and theoretical foundations for physical simulations. The project targets applications in fields of federal strategic interest, including nanoscale material design for electronic devices and plasma control for nuclear fusion energy production. The work resolves three significant technical challenges: closing the fidelity gap compared to diffusion models, reducing high computational complexities during sampling, and establishing rigorous application-driven validation loops. Performance runs from September 1, 2026, through August 31, 2029, at the University of Utah's Salt Lake City campus. Beyond the core research, the award supports training of three to four doctoral students and funds curriculum development in data science and stochastic computation. The project disseminates open-source software and research findings through international workshops to build a skilled STEM workforce.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $250.0k | 7/31/26 |