The National Science Foundation (NSF) awarded a $327,311 Project Grant under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) to Trustees of Dartmouth College to conduct collaborative research on connections between optimization methods and property testing for processing large data sets and developing accurate predictive models. The three-year project, which began on April 1, 2024, aims to discover mathematical relationships between sublinear...
This $118,760 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will support research to advance the state-of-the-art in optimization theory and algorithms for modern data science problems. The 5-year project at The Johns Hopkins University aims to develop novel tools to analyze the computational and statistical complexity of optimization heuristics, and design new algorithms that can better leverage the inherent...
This $300,000 federal Project Grant award from the National Science Foundation's (NSF) Division of Mathematical Sciences will fund research to develop new mathematical techniques for optimization in the context of big data and contemporary data science challenges. The principal investigator at Cornell University will lead this 3-year project, which aims to transform the design and analysis of optimization algorithms across diverse fields including machine learning, statistics, and control...
This $443,217 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research on fast combinatorial algorithms for graph problems such as maximum matching, maximum flow, and shortest paths. The award aims to develop new algorithms for dynamic graphs, where the graph structure changes over time, as well as improve expander-related tools that can serve as building blocks for many graph algorithms....
This $250,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports research by the University of California, San Diego (UCSD) on the development of "tight relaxation methods" for solving challenging optimization problems, such as polynomial optimization, generalized Nash equilibria, and matrix-constrained polynomial optimization. The project aims to create efficient computational methods for locating global...
The National Science Foundation Division of Computing and Communication Foundations awarded a $274,242 Project Grant to Northeastern University on June 15, 2021 with a completion date of October 31, 2023. The grant is part of the Computer and Information Science and Engineering program (CFDA 47.070), which supports investigator-initiated research and education in all areas of computing, communications, and information science and engineering. Under this award, Northeastern University will...
This $248,882 federal Project Grant, awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program on June 1, 2024, supports research to address the "curse of dimensionality" in high-dimensional geometric optimization problems. The project, led by the University of Pennsylvania, aims to develop efficient algorithms and foundational principles for solving challenging geometric optimization problems that become intractable as data...
This $255,353 National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) Project Grant awarded to Northeastern University will fund research on sublinear-time graph algorithms. The project aims to develop more efficient and optimal sublinear-time algorithms for foundational graph problems, understand the limitations of these algorithms through query lower bound analysis, and explore connections to other computation models like dynamic, parallel, and...
This Project Grant award of $245,755 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) supports research by the Regents of the University of California at Riverside (UC Riverside) to develop new mathematical frameworks and algorithms for approximating solutions to constraint satisfaction problems (CSPs). The research aims to advance the theoretical understanding of optimization and computation by leveraging deep...
The University of California, Davis (UC Davis) received a $255,127 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to advance the design of efficient, large-scale graph algorithms. The project aims to develop innovative methods and more efficient algorithms for processing massive graphs by investigating sparsification techniques in parallel and distributed computational frameworks. This 5-year research...