Project Grant 2502259
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049) provides $240,000.00 to The Trustees of Columbia University in the City of New York to develop methods that enhance trust and control over machine learning (ML) and artificial intelligence (AI) technologies. The project aims to create computationally efficient algorithms that can approximate the output of an ML model trained without a given subset of...
- This $162,000 federal Project Grant awarded by the National Science Foundation (NSF) under the Mathematical and Physical Sciences program (CFDA 47.049) is supporting collaborative research at the University of California, San Diego (UCSD) to build mathematical foundations for reasoning about the behavior of modern machine learning systems. The goal is to develop a mathematical theory of how features emerge in AI models in order to demystify model performance, reveal limitations, and guide the...
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049) provides $150,000 to the University of Washington to conduct research into the mathematical foundations of advanced generative artificial intelligence (AI) models. The overarching goal is to uncover the mathematical principles underlying the remarkable performance of frontier AI models like large language models, in order to overcome current limitations and...
- This three-year, $260,000 Project Grant from the National Science Foundation's Division of Mathematical Sciences, under the Mathematical and Physical Sciences program (CFDA 47.049), will fund research towards designing optimal statistical learning procedures through precise medium-dimensional asymptotic analysis. The grantee, Columbia University, will develop a novel analytical framework to quantitatively characterize the performance of diverse learning algorithms and provide guidance on...
- The Trustees of Columbia University in New York City received a $499,756 Project Grant award from the National Science Foundation Division of Information and Intelligent Systems. The grant is part of the NSF's Computer and Information Science and Engineering program (CFDA #47.070) to support investigator-initiated research and education across computing, communications, and information science and engineering fields. Specifically, the October 1, 2021 award will fund research into "New...
- This $296,023 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports research to establish the mathematical foundations of two models that underpin generative artificial intelligence (AI) methodologies in scientific contexts: score-based generative models and transformer-based foundation models. The primary goals of this 5-year project are to study the role of fine data structures in mitigating the curse of...
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences Program (CFDA 47.049) provides $1,323,521 to Auburn University and Tuskegee University to conduct collaborative research on building a robust mathematical foundation for artificial intelligence (AI) and integrated data science. The 5-year project, which began on September 1, 2025, will train undergraduate students, graduate students, and postdoctoral researchers to conduct advanced research...
- This $322,400 federal Project Grant awarded by the National Science Foundation's (CFDA 47.070) Computer and Information Science and Engineering program supports the development of artificial intelligence (AI) systems capable of accelerating mathematical research and theorem-proving at scale. The goal is to create an AI system that can tackle unsolved problems and prove graduate-level mathematical theorems, which would serve the national interest by driving scientific discovery across fields like...
- The National Science Foundation (NSF) awarded a $350,000 Project Grant under the Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049) to The Johns Hopkins University. The grant, titled "ANY-DIMENSIONAL EQUIVARIANT LEARNING -MODERN ARTIFICIAL INTELLIGENCE (AI) SYSTEMS PROVIDE A VERSATILE TOOLKIT FOR IDENTIFYING SOLUTION MAPS FOR A VARIETY OF PROBLEMS IN A DATA-DRIVEN FASHION," will support research to develop algorithms that can handle input data of varying dimensions,...
- This $148,654 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program supports collaborative research to develop statistical tools for improving the reliability of artificial intelligence (AI) systems. The research aims to establish mathematically rigorous methods for uncertainty quantification to build trustworthy AI with applications in automated decision-making, financial forecasting, and neuroscience research. The work will focus on...
The National Science Foundation (NSF) awarded a $163,000 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to The Trustees of Columbia University in the City of New York, doing business as Columbia University. The goal of this 3-year research project, from October 1, 2025 to September 30, 2028, is to build mathematical foundations for reasoning about the behavior of modern machine learning systems. The research focuses on understanding how artificial intelligence (AI) models represent and learn from data, with the aim of demystifying model performance and limitations. This includes developing general principles for how features emerge in AI models and studying these principles in analytical architectures like multilayer perceptrons, kernel methods, and transformers. The research seeks to guide the development of next-generation AI models that can overcome the limitations of current approaches.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $163.0k | 7/21/25 |