Project Grant 2552046
Award Date 8/1/26
Completion Date 7/31/30
Dollars Obligated $500K
Funding Federal Agency
Awarding Federal Agency
Federal Grant Program
Assistance Type
Project Grant
Place of Performance
Cambridge, MA 02139, USA
Similar Awards
- The National Science Foundation Division of Computing and Communication Foundations awarded New York University $500,000 on August 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop theoretically sound and scalable deep reinforcement learning methods for imperfect-information games—settings where decision makers must act without full knowledge of others' information states. The project delivers three primary components: sound policy-gradient...
- The National Science Foundation Division of Computing and Communication Foundations awarded Massachusetts Institute of Technology $360,000 on July 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) for self-supervised video representation learning for machine perception. The project develops a self-supervised framework for video representation learning that separates efficient perception modules from generative world models to extract compact...
- The National Science Foundation Division of Computing and Communication Foundations awarded $800,000 under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) to the University of California, Berkeley for a four-year collaborative research project grant. The project aims to improve the sample efficiency of reinforcement learning algorithms in both offline and online settings through techniques like optimistic exploration and pessimistic exploitation. It...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) Project Grant award of $600,000 to the Massachusetts Institute of Technology (MIT) supports research into developing better algorithms for machine learning problems that involve sequential data with rich dependency structures. The project will explore learning methods for linear dynamical systems, graphical models, and hidden Markov models, with the goal of proving rigorous theoretical...
- The National Science Foundation Division of Information and Intelligent Systems awarded Massachusetts Institute of Technology $850,000 on October 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to investigate whether AI agents can assist in the expert-level design of networked systems. The project studies how large language models and AI systems capable of experimentation, reasoning, and hypothesis formation can participate in the design work currently...
- The National Science Foundation Division of Computing and Communication Foundations awarded the University of Southern California $871,225 on August 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop theoretical foundations for multi-agent learning systems in artificial intelligence. The project advances the theory of online optimization and learning within multi-agent systems through three research thrusts. The first thrust characterizes optimal...
- The National Science Foundation Division of Electrical, Communications and Cyber Systems awarded Massachusetts Institute of Technology $659,678 on April 1, 2026, under the CAREER: Trustworthy Learning-Enabled Autonomy project grant (NSF Engineering, CFDA 47.041). The project develops mathematical theory and efficient algorithms that allow autonomous systems to learn from data while reliably respecting safety constraints. The work addresses vulnerabilities in learning-enabled vehicles, robots,...
- This federal Project Grant award of $227,984.00, awarded on January 15, 2025 by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports research by the Massachusetts Institute of Technology (MIT) to advance the theoretical and practical understanding of equilibrium computation and learning dynamics in multi-agent interactions, such as in military, security, and auction settings. The project aims to develop new algorithms and...
- The National Science Foundation Division of Information and Intelligent Systems awarded Georgia TECH Research Corp $600,000 on September 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop formal reasoning methods for reinforcement learning systems deployed in safety-critical applications. The project addresses the problem of reward hacking in reinforcement learning agents used in autonomous vehicles, robotic surgery, and autonomous trading, where...
- This $600,000 National Science Foundation project grant supports research at Stony Brook University to develop a suite of novel distributed reinforcement learning algorithms. The grant is funded through the NSF's Computer and Information Science and Engineering program. Specifically, the three-year award will fund research to establish theoretical foundations for designing, analyzing, and applying fully distributed reinforcement learning algorithms over large-scale networks without global...