This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $480,225.00 to the University of Illinois to support foundational research on nonlinear filtering and reinforcement learning (RL) algorithms. The goal is to develop new methods for analyzing the stability of nonlinear filters and apply these techniques to create a new class of efficient RL algorithms. The research plan has two main parts: 1) Developing stochastic stability theory...
This Project Grant from the National Science Foundation's $366,083 Engineering program will fund research at the University of Washington to develop a theoretical and algorithmic framework for reliably combining heterogeneous and asynchronous sensor data streams to achieve fast situational awareness and robust feedback response. The research aims to advance foundational knowledge for designing next-generation critical systems that assist humans in data-intensive situations. Specifically, the...
This Project Grant award from the National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems supports research to develop low-complexity, safe learning-enabled algorithms for partially observable nonlinear systems with uncertain dynamics. The $400,000 award to Michigan State University aims to accomplish two key objectives: 1) Propose direct data-driven learning approaches for backup safe control policies in partially observable nonlinear systems, and 2) Introduce...
This National Science Foundation Project Grant award of $287,406 provides funding from July 1, 2022 through June 30, 2027 to support research at the University of California, Santa Barbara exploring optimal transport and dynamics in machine learning. The Principal Investigator will study the mathematical foundations of machine learning using tools from optimal transport and partial differential equations. Three main research projects will be conducted. The first will analyze nonlocal...
This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $199,369 to the University of Wyoming to develop a framework for enabling autonomous systems to detect, classify, and mitigate unexpected disruptions in real-time. The research aims to create a unified approach using game-theoretic modeling and reinforcement learning to enhance the resilience, efficiency, and safety of autonomous systems in critical applications such as...
This National Science Foundation Project Grant of $315,519 supports research at the University of California, Los Angeles from July 2022 to June 2025 under the Mathematical and Physical Sciences program (CFDA 47.049). The award funds research investigating challenging problems in optimal transport theory and its applications in fields including partial differential equations, geometry, probability, and machine learning. Key areas of focus include developing the theory to analyze games with large...
The National Science Foundation awarded a $400,000 Project Grant to the University of Washington under the Engineering program (CFDA 47.041) to develop data-guided system-theoretic techniques for control of dynamic systems from August 15, 2022 to July 31, 2025. Specifically, the award will support research to extend the current data-guided control paradigm to nonlinear systems and networked systems through novel data-parameterized analysis and synthesis methods. The research will also examine...
This $297,881 project grant awarded by the National Science Foundation's Engineering Program (CFDA 47.041) supports research to advance the theory and algorithms for distribution control, enabling precision manufacturing of materials and coordination of autonomous agents. The key objectives are to address challenges in nonlinearity, agent interactions, and control policy robustness, with the goal of delivering scalable computational methods for distribution control with optimality and robustness...
This National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems award, CFDA 47.041 Engineering, will provide $193,000 from September 1, 2024 to August 31, 2027 to New York University (NYU) to develop new theories and methodologies for safe reinforcement learning in domains such as robotics, autonomous driving, and power systems. The key products and services to be delivered under this Project Grant include: 1) Formulating safety measures as general objectives...
The National Science Foundation (NSF) awarded a Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) federal grant program to North Carolina State University (NC State) in the amount of $113,834. The grant, titled "COLLABORATIVE RESEARCH: AF: SMALL: EFFICIENT ALGORITHMS FOR OPTIMAL TRANSPORT IN GEOMETRIC SETTINGS," aims to advance the theoretical underpinnings and develop simple, scalable algorithms for computing high-quality optimal transport plans of...