Project Grant 2541280
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Mathematical Sciences awarded $300,000 to the University of California, Los Angeles (UCLA) under the Mathematical and Physical Sciences program (CFDA 47.049) on January 15, 2026, with a completion date of December 31, 2028. This Mathematical Foundations of Artificial Intelligence (MFAI) project delivers foundational research on the critical relationship between data and large language models (LLMs), addressing how data...
- Federal Grant Award Summary The National Science Foundation's Division of Computing and Communication Foundations awarded a $349,963 CAREER grant to Toyota Technological Institute at Chicago (TTIC) on June 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070). The project, which runs through May 31, 2031, will develop foundational optimization theory for deep learning systems by establishing scientific principles that link optimization methods to neural...
- Federal Grant Award Summary The National Science Foundation's Division of Computing and Communication Foundations awarded a five-year CAREER grant totaling $301,560 to Florida State University (effective October 1, 2026 through September 30, 2031) under the Computer and Information Science and Engineering program (CFDA 47.070). The project develops the Large Number Model (LNM), a hybrid neural-symbolic artificial intelligence system designed to reliably process complex numerical and structured...
- Federal Project Grant Award Summary The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $400,000 Project Grant to Harvard College, effective June 1, 2026 through May 31, 2029, to develop novel tensor decomposition algorithms for multi-context data analysis. Under CFDA 47.049 (Mathematical and Physical Sciences), the investigator will design and implement new tensor decomposition methods with rigorous theoretical guarantees, addressing a fundamental challenge in...
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Mathematical Sciences awarded $330,000 to the University of California, Los Angeles under the Mathematical and Physical Sciences program (CFDA 47.049) effective January 15, 2026, with completion targeted for December 31, 2028. This Project Grant funds the development of randomized algorithms for operator learning that enable efficient approximation of solution operators for parametric partial differential equations...
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Mathematical Sciences awarded $255,237 to the University of Minnesota under the Mathematical and Physical Sciences (CFDA 47.049) program for a collaborative research project running from September 1, 2025, through August 31, 2028. This project focuses on developing acceleration and preconditioning methods to optimize deep learning (artificial intelligence) model training processes. The research leverages numerical...
- Federal Project Grant Award Summary The National Science Foundation's Division of Mathematical Sciences awarded $296,023 to the Regents of the University of Minnesota under the Mathematical and Physical Sciences program (CFDA 47.049) effective August 1, 2025, through July 31, 2030. This CAREER award supports fundamental research establishing the mathematical foundations of two critical generative artificial intelligence (AI) models: score-based generative models and transformer-based...
- Federal Grant Award Summary The National Science Foundation (NSF) awarded The Leland Stanford Junior University a $677,600 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) effective September 15, 2025, with a completion date of August 31, 2028. The project, titled "AIMING: AI Theorem Proving Beyond Limited Data: Efficient Learning of Mathematicians' Ecosystem," develops artificial intelligence (AI) systems designed to accelerate mathematical research and...
- Federal Grant Award Summary The National Science Foundation (NSF), Division of Mathematical Sciences, awarded a $175,000 Project Grant (CFDA 47.049, Mathematical and Physical Sciences) to Harvard College, effective July 1, 2026, through June 30, 2029. This award funds the development of mathematical and computational frameworks for integrating high-dimensional datasets with partially shared structures. The project will establish new theoretical foundations at the intersection of random matrix...
- Federal Grant Award Summary The National Science Foundation's Division of Mathematical Sciences awarded a five-year CAREER grant of $243,000 to Columbia University beginning September 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049). This project develops a statistical framework for evaluating uncertainty quantification and principled design of generative artificial intelligence (AI) systems. The research pursues three primary thrusts: (1) measuring overall fidelity of...
The National Science Foundation (NSF) Division of Mathematical Sciences awarded $300,000 to Trustees of Tufts College under the Mathematical and Physical Sciences program (CFDA 47.049) to support the CAREER project "TENAI: Tensorizing Machine Learning to Leverage Multiway Structure." This five-year award, effective September 1, 2026 through August 31, 2031, funds fundamental research aimed at advancing machine learning scalability and interpretability through tensor-based methodologies. The project will develop novel mathematical frameworks that exploit multidimensional data correlations and hidden multiway structures—such as spatio-temporal relationships—to create more efficient, transparent, and computationally sustainable artificial intelligence (AI) tools suitable for high-consequence applications including drug discovery and cybersecurity. Deliverables under this award include the development of tensorization strategies that will establish theoretically sound foundations for machine learning, creation of improved data featurizers leveraging multilinear operations, and low-rank interpretable representations for efficient high-dimensional space approximation. The project also encompasses substantial educational components designed to cultivate the next generation of computational mathematicians and data scientists, preparing them for leadership roles in an AI-enhanced workforce. By combining fundamental mathematical research with workforce development, this CAREER award supports both scientific innovation and human capital development in computational mathematics and data science.Federal Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $300.0k | 5/20/26 |