Project Grant 2442418
Award Date
9/1/25
Completion Date
8/31/30
Dollars Obligated
$438K
Federal Agency
Division of Electrical, Communications and Cyber Systems
Federal Grant Program
47.041
Assistance Type
Project Grant
Place of Performance
Buffalo, NY 14228, USA
Similar Awards
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...
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 $438,342 Project Grant awarded by the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports research to develop efficient and rigorous techniques for solving complex, multi-objective decision-making problems under uncertainty. The research aims to facilitate tradeoffs among multiple objectives while using statistically valid algorithms to achieve high efficiency. Key approaches include novel comparison techniques, data recycling, computer simulation, and parallel...
This $299,997 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, CFDA 47.070, will support research to improve multiobjective optimization tools. The project aims to develop new deterministic methods to efficiently explore the Pareto front, which represents the trade-offs between conflicting goals in complex optimization problems. This includes finding solutions that balance objectives like safety, fuel efficiency,...
This $318,590 Project Grant awarded by the National Science Foundation (NSF) Engineering Program (CFDA 47.041) supports research and development at the Georgia Tech Research Corporation aimed at advancing computational models and algorithms for distributed constrained optimization in complex multi-agent networks. The key objectives are to: (i) develop an enhanced mathematical modeling framework utilizing variational inequality theory; (ii) design and analyze new iteratively regularized...
This Project Grant award of $450,000 from the National Science Foundation's Engineering program (CFDA 47.041) will support research on bi-level optimization for hierarchical machine learning problems. The award to the Regents of the University of Minnesota, conducting the work through their Office of Sponsored Projects Administration, aims to develop new approaches for modeling, analyzing, and innovating on a wide array of emerging machine learning applications using bi-level optimization...
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...
This $591,545 Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CFDA 47.070) program will fund research to develop algorithms for generating diverse sets of high-quality solutions to optimization problems. The principal investigator and their team at the Research Foundation of the City University of New York will investigate diverse solution generation for three fundamental computer science problems: satisfiability of k-CNF formulas,...
The National Science Foundation awarded a $346,983 Project Grant to the University of Connecticut (UConn) under the NSF's Engineering program (CFDA 47.041) to develop scalable deterministic global optimization (DGO) algorithms and open-source software. The project aims to enable the solution of higher complexity models involving nonlinear equations by exploiting parallel computing architectures like graphical processing units (GPUs). The research will generate methods for automatically...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award of $111,723 to The Research Foundation For The State University Of New York, doing business as Stony Brook University, will fund a 5-year project titled "CAREER: Structured Learning and Optimization for Efficient Resource Management in the Wireless Edge Cloud: Theory and Algorithms". The project aims to develop structured learning and optimization...