Project Grant 2550249
- Federal Project Grant Award Summary The National Science Foundation's Office of Multidisciplinary Activities awarded $500,000 under the Social, Behavioral, and Economic Sciences program (CFDA 47.075) to the University of California, San Diego to develop a Large Language Model (LLM)-Based Smart Learning Hub for computing education. The project, which commenced on October 1, 2025, and will conclude on September 30, 2028, aims to create an integrated pedagogical tool that leverages artificial...
- Federal Grant Award Summary Award Details: The National Science Foundation (NSF) Division of Information and Intelligent Systems awarded $174,592 to the University of Dayton Research Institute Division under the Computer and Information Science and Engineering (CFDA 47.070) program. The project commenced on July 1, 2025, with an anticipated completion date of June 30, 2027. Products and Services: This Computer Research Initiation (CRII) project develops an AI-powered educational game platform...
- Federal Grant Award Summary The National Science Foundation (NSF), Division of Mathematical Sciences, awarded The Leland Stanford Junior University a $174,629 project grant effective February 1, 2026, through January 31, 2029, under the Mathematical and Physical Sciences program (CFDA 47.049). This CAREER award funds the development of novel learning frameworks and mathematical foundations for large-scale stochastic games, specifically advancing mean-field game theory applicable to modern...
- Federal Grant Award Summary The National Science Foundation (NSF) awarded UC San Diego a $100,000 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) effective August 1, 2025, through July 31, 2028. This collaborative research initiative focuses on developing theoretical tools to advance understanding of diffusion and flow-based generative models through geometric perspectives. The project aims to elucidate the fundamental mechanisms underlying these artificial...
- Federal Grant Award Summary The National Science Foundation's Division of Computing and Communication Foundations awarded $450,000 under the Computer and Information Science and Engineering (CFDA 47.070) program to the Regents of the University of California at Riverside for a three-year project (October 1, 2025 – September 30, 2028). The project develops research outputs focused on integrating Large Language Models (LLMs) with existing program analysis tools to improve software vulnerability...
- Federal Grant Award Summary The National Science Foundation's Division of Computing and Communication Foundations awarded a $600,000 Project Grant to the University of California, San Diego under the Computer and Information Science and Engineering program (CFDA 47.070) for the period July 1, 2026 through June 30, 2029. The award supports research into selective prediction techniques for large visual-language models designed to improve the trustworthiness and safety of artificial intelligence...
- Federal Project Grant Award Summary New York University received a $300,000 Project Grant from the National Science Foundation (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070), awarded October 1, 2025, with a completion date of July 31, 2028. This collaborative research initiative addresses critical evaluation gaps in Large Language Models (LLMs) by developing a comprehensive set of "evaluation...
- Federal Grant Award Summary This $174,999 Project Grant award, issued September 1, 2025, by the National Science Foundation's Division of Computing and Communication Foundations under the Computer and Information Science and Engineering program (CFDA 47.070), supports a unified Large Language Model (LLM)-empowered framework for systematic software performance issue testing, localization, and optimization at California State University Long Beach Research Foundation. The project will deliver...
- 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's STEM Education program (CFDA 47.076) awarded $1,299,797 to the University of California, Berkeley (UC Berkeley) on September 15, 2025, to develop and test an innovative model for engaging youth in the co-design of artificial intelligence (AI) museum exhibits. Administered through the Division of Research on Learning in Formal and Informal Settings, this project grant will operate through August 31, 2029, and will empower up to 100...
The National Science Foundation (NSF) awarded the University of California, San Diego $1,494,278 under the Technology, Innovation, and Partnerships program (CFDA 47.084) for Phase II of the LMGAME project, effective July 15, 2026, through June 30, 2028. The award funds the development and operationalization of LMGame, an integrated open-source ecosystem that leverages computer games as standardized benchmarking and training instruments for evaluating generative artificial intelligence (AI) capabilities. The ecosystem consolidates diverse game environments under a unified Large Language Model (LLM)-first platform with shared application programming interfaces (APIs), standardized metrics, and reproducible testing harnesses to enable rigorous evaluation of AI reasoning, planning, perception, and decision-making capabilities. The project delivers four coordinated components: (1) a consolidated evaluation and training platform integrating all game environments and shared APIs; (2) formalized governance through a Technical Core Committee with versioned release management and responsible-disclosure processes; (3) continuous development and deployment infrastructure with reproducible test harnesses for each game and metric; and (4) ecosystem expansion through partner pathways for academia, industry, and other stakeholders. By establishing coherent open-source infrastructure for trustworthy AI evaluation, LMGame addresses critical national needs in AI transparency, researcher capacity-building, and U.S. leadership in open-source AI development.Federal Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $1.5m | 7/7/26 |