Project Grant 2514157
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $331,902 Project Grant to the Trustees of Boston University on August 15, 2023 under the Mathematical and Physical Sciences program (CFDA 47.049). The purpose of this 3-year grant is to develop rigorous mathematical analysis and theory for the training algorithms used in neural network models across various machine learning applications. The research will leverage stochastic analysis and weak convergence theory...
- This National Science Foundation award provides $399,998 to the University of California, Los Angeles under the Mathematical and Physical Sciences program (CFDA 47.049) for the period of July 1, 2022 through June 30, 2025. The project will develop new algorithms and mathematical theory for multi-agent sequential deep learning using insights from ordinary and partial differential equations. Researchers will integrate advances in neural ordinary differential equations with graph networks to build...
- Federal Grant Award Summary The National Science Foundation (NSF) awarded $375,000 to the University of California, Los Angeles through the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) on August 15, 2025, with completion targeted for July 31, 2028. This collaborative research project, managed through NSF's Division of Computing and Communication Foundations, focuses on developing specialized theoretical frameworks and practical algorithms for min-max...
- Federal Grant Award Summary The University of California, Los Angeles received a $128,920 Project Grant award effective January 1, 2026, through December 31, 2028, funded by the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). This collaborative research initiative aims to advance artificial intelligence (AI) and mathematics through synergistic computational methods that...
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Civil, Mechanical, and Manufacturing Innovation awarded a $750,000 project grant (CFDA 47.041: Engineering) to the University of California, Los Angeles, effective January 15, 2026, with completion targeted for December 31, 2028. This Mathematical Foundations of Artificial Intelligence (MFAI) project delivers foundational research and mathematical frameworks addressing the critical relationship between data and large...
- This $299,889 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports research at the University of California, San Diego (UCSD) to develop algorithms for compressing and improving the efficiency of large neural networks used in modern artificial intelligence applications. The key products and services to be delivered include: The research project focuses on developing quantization, pruning, and low-rank...
- The National Science Foundation (NSF) awarded a $800,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of California, Los Angeles (UCLA) - Office of Research Administration. The grant, titled "COLLABORATIVE RESEARCH: III: MEDIUM: VIRTUALLAB: INTEGRATING DEEP GRAPH LEARNING AND CAUSAL INFERENCE FOR MULTI-AGENT DYNAMICAL SYSTEMS", will fund the development of a virtual laboratory framework to model and predict the...
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $107,860 Project Grant to the Regents of the University of Minnesota, Office of Sponsored Projects Administration, a non-profit 1862 land grant college, to conduct research under the NSF Mathematical and Physical Sciences program (CFDA 47.049). The research project will develop theoretical foundations for using machine learning methods to solve high-dimensional partial differential equations, emphasizing predictive...
- Federal Grant Award Summary The National Science Foundation's Division of Mathematical Sciences awarded $162,576 to the University of California, Los Angeles under the Mathematical and Physical Sciences program (CFDA 47.049) on April 1, 2025, for a project titled "Interacting Particle System for Nonconvex Optimization." The award, with a completion date of June 30, 2027, supports fundamental research in optimization methods that leverage collective intelligence principles from...
- This $293,784 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports fundamental and applied research on fluctuating systems, random environments, and stochastic algorithms. The research aims to improve understanding and exploitation of randomness across diverse settings, including materials science, fluid dynamics, and machine learning. Key areas of focus include stochastic homogenization, stochastic partial...
The National Science Foundation (NSF) Division of Mathematical Sciences awarded $330,000 to UCLA under the Mathematical and Physical Sciences program (CFDA 47.049) on January 15, 2026, for research on randomized algorithms for operator approximations in Sobolev spaces. This project delivers theoretical and computational tools designed to improve the efficiency of machine learning and artificial intelligence (AI) applications in scientific modeling, specifically by developing tractable training algorithms that can solve parametric partial differential equations (PDEs) in resource-constrained environments. The research addresses a critical limitation in current operator learning approaches: as neural networks grow in complexity to capture dependencies on input parameters, domain configurations, and boundary conditions, computational resource and memory constraints become prohibitive. The project will produce rigorous theoretical analysis including quantitative bounds on model complexity, approximation accuracy, and generalization error, with particular emphasis on training algorithms suitable for noisy and limited data settings. Beyond direct research deliverables, this project (scheduled for completion December 31, 2028) will contribute to curriculum development in mathematics at both graduate and undergraduate levels and provide training support for graduate students. The outcomes are expected to broaden the applicability of machine learning methodologies in scientific computation and modeling applications. No sub-awards are planned for this project, with all work being performed at UCLA's Los Angeles, CA location.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $330.0k | 1/5/26 |