Project Grant 2515978
- This National Science Foundation (NSF) Engineering program (CFDA 47.041) award of $250,000.00 to the University of Arizona provides funding for a collaborative research project on "Efficient Bilevel Optimization Methods for Planning and Control." The project aims to develop scalable algorithms for constrained, nonconvex bilevel optimization problems, with a focus on enabling safe, real-time decision-making in planning and control tasks for robotics, machine learning, and autonomous...
- The National Science Foundation (NSF) awarded a three-year, $300,190 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to The Research Foundation for the State University of New York (RF SUNY) to conduct collaborative research on large-scale bilevel optimization. The key objectives are to develop fast and scalable Hessian-free bilevel optimization algorithms, analyze primal-dual and pessimistic bilevel methods, and devise algorithms for solving...
- This Project Grant award of $299,549 from the National Science Foundation's (NSF) Division of Computing and Communication Foundations, under the Computer and Information Science and Engineering program (CFDA #47.070), provides funding to William Marsh Rice University to conduct collaborative research on large-scale bilevel optimization problems. The project aims to develop new theory, algorithms, and applications for bilevel optimization, which has important implications for emerging fields like...
- The National Science Foundation (NSF) awarded a 3-year, $249,965 Project Grant to William Marsh Rice University under the Engineering federal grant program (CFDA 47.041) to develop new algorithms for solving bilevel optimization problems in multi-agent distributed systems. The project aims to close the gap between existing bilevel optimization research focused on single-agent systems and the growing need to solve such problems in distributed networks, such as those arising in power systems,...
- This $118,760 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program to The Johns Hopkins University. The goal of this 5-year CAREER award is to advance the state of the art in optimization theory and algorithms to tackle the unique challenges posed by modern data science problems. The research will develop novel tools to analyze the computational and statistical complexity of optimization...
- The National Science Foundation (NSF) awarded a $250,000 Project Grant under the Engineering program (CFDA 47.041) to the University of California, Davis (UC Davis) for the period of September 1, 2024 to August 31, 2027. The grant supports the development of an online bilevel optimization framework to address modern challenges in signal processing and machine learning, such as multi-task learning, sequential decision making, and robust adversarial training. The research innovations include...
- The University of Arizona was awarded a $224,375 project grant from the National Science Foundation Division of Electrical, Communications and Cyber Systems. The grant supports collaborative research on computationally efficient algorithms for large-scale bilevel optimization problems under the NSF Engineering program (CFDA 47.041). The Engineering program aims to improve quality of life and economic strength by fostering innovation in engineering research. This project specifically develops new...
- The National Science Foundation (NSF) Directorate for Engineering (ENG) awarded a $250,000 Project Grant to The Research Foundation for The State University of New York (RF SUNY) for the period of August 15, 2023 to July 31, 2026. The grant, titled "COLLABORATIVE RESEARCH: DISTRIBUTED BILEVEL OPTIMIZATION IN MULTI-AGENT SYSTEMS," aims to develop new algorithms for solving bilevel optimization problems over multi-agent distributed networks. The project will focus on three main...
- This Project Grant award for $525,000.00 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of specialized theoretical frameworks and efficient algorithms for min-max optimization. This research aims to significantly enhance the efficiency and robustness of min-max optimization, with direct impacts on practical applications in machine learning and artificial intelligence. The project, awarded to The Johns...
- The National Science Foundation Division of Electrical, Communications and Cyber Systems awarded a $224,375 Project Grant to the University of Texas at Austin from September 15, 2021 through August 31, 2024. The grant supports collaborative research to develop computationally efficient algorithms for large-scale bilevel optimization problems under the NSF Engineering program (CFDA 47.041). The Engineering program seeks to improve quality of life and economic strength by fostering innovation...
This federal Project Grant award, valued at $273,797 and granted by the National Science Foundation's (NSF) Division of Electrical, Communications and Cyber Systems, aims to develop efficient and scalable algorithms for constrained, nonconvex bilevel optimization problems, with a focus on planning and control tasks in safety-critical domains. The research comprises two main thrusts: (1) designing a novel control-theoretic framework to systematically develop bilevel solvers with provable convergence guarantees and anytime safety, and (2) targeting scalability, non-unique lower-level solutions, and nonconvexities in bilevel optimization. The outcomes of this 3-year project (10/1/2025 - 9/30/2028) will provide general-purpose optimization tools that can benefit a broad range of applications in robotics, learning, and autonomous systems. The award was granted to The Johns Hopkins University, a private, non-profit research institution renowned for its excellence in academic research, medical innovation, and scientific discovery.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $273.8k | 7/30/25 |