Project Grant 2145553

CAREER: Safety-Centered Multi-Agent Reinforcement Learning Wake Forest University received $520,013 in Project Grant funding from the National Science Foundation's Division of Information and Intelligent Systems (CFDA 47.070) awarded on July 15, 2025, with a completion date of June 30, 2030. This CAREER award supports research and development of a comprehensive safety framework for multi-agent reinforcement learning (MARL) systems. The project delivers four key innovations: (1) learning...

This $349,427 CAREER grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research at The Leland Stanford Junior University (Stanford University) to develop machine learning (ML) techniques to improve the performance of discrete optimization algorithms. The project aims to address challenges in efficiently solving complex combinatorial optimization problems, such as those encountered in supply chain logistics and...

This three-year, $500,000 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program will fund research at the University of California, Davis to develop trustworthy machine learning systems through adversarial robust reinforcement learning. Specifically, the award supports investigating potential vulnerabilities in reinforcement learning models and algorithms, developing robust RL approaches that mitigate impacts from adversarial attacks, and...

This $299,999 Project Grant awarded by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to enhance the performance of reinforcement learning (RL) systems in completing complex tasks in challenging environments. The project aims to develop new task and environment representations to enable active learning strategies that optimize resource allocation and reduce the need for extensive physical interactions with the...

This Project Grant from the National Science Foundation's Division of Computing and Communication Foundations, under the Computer and Information Science and Engineering program (CFDA 47.070), provides $300,000 to support research and education activities at Stanford University from October 1, 2022 to September 30, 2025. The award will fund the development of new algorithms for decision tree learning and the establishment of rigorous mathematical guarantees for existing algorithms widely used in...

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...

This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will fund a $174,965 project at the College of William & Mary in Williamsburg, Virginia. The project, titled "CRII: III: REINFORCEMENT LEARNING FOR COMBINATORIAL OPTIMIZATION IN SOCIETAL PROBLEMS," aims to develop innovative artificial intelligence (AI) technologies to efficiently solve complex real-world combinatorial optimization...

This Project Grant award from the National Science Foundation (NSF) Office of Advanced Cyberinfrastructure under the CFDA program "Computer and Information Science and Engineering" provides $150,000 to Duke University to conduct collaborative research on developing efficient and provable algorithms for approximate sampling-based exploration strategies in sequential decision-making problems. The key objectives are to unify exploration strategies across different applications like...

This $412,038 CAREER (Careers in Teaching and Research) award from the National Science Foundation's Division of Computing and Communication Foundations under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports a five-year research project at Boston University running from October 1, 2025, through September 30, 2030. The project develops improved approximation algorithms for NP-hard graph problems that are computationally intractable to solve exactly. The...

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...