The National Science Foundation awarded a $250,000 project grant to Georgia Tech Research Corporation under the Mathematical and Physical Sciences program (CFDA 47.049) for the period of August 1, 2023 through July 31, 2026. The grant funds the development of experimental design-based weighted sampling techniques that introduce weights for each sample to improve upon existing sampling methods for quantifying population characteristics. The Principal Investigator will develop software packages to...
This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports research on efficient sampling algorithms for target probability distributions. The key objectives are to: Develop a theoretical framework to analyze the long-term convergence properties of sampling dynamics characterized by kinetic equations. Use techniques from optimization, optimal transport, and applied analysis to study sampling dynamics structured as...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will support $122,000 in research over a 5-year period, starting on June 1, 2025 and ending on May 31, 2030. The goal of this award is to develop new mathematical tools and techniques for analyzing sampling algorithms used ubiquitously in practice for manipulating and understanding complex, high-dimensional probability distributions. This research will focus on...
This $313,927 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will support research on random sampling methods for analyzing large systems and their potential applications, such as detecting gerrymandering. The primary goals are to develop new random sampling techniques, analyze existing methods, and identify problems amenable to these approaches. This includes adapting statistical physics concepts to...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) (CFDA 47.070) Project Grant award of $108,000 to the Georgia Tech Research Corp, Office of Sponsored Programs, will fund collaborative research to develop a unified framework for analyzing adaptive stochastic optimization methods for machine learning applications. The research aims to produce self-tuning optimization algorithms with rigorous guarantees to reduce wasteful computation required by current...
This $350,000 Project Grant award from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) supports collaborative research to develop cost-efficient and confidence-building sampling methods for modern scientific discovery. The award to the Illinois Institute of Technology (IIT) aims to create a framework featuring new methodologies, theory, and algorithms that extend classical low-discrepancy sampling...
This federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, with CFDA number 47.070, provides $661,515.00 in funding to Georgia Tech Research Corp to conduct collaborative research on fundamental challenges in discrete and continuous optimization. The research aims to develop new techniques that enable faster and more accurate algorithms for modern AI and scientific computing applications. Key research thrusts...
The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $100,000 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to the Georgia Tech Research Corporation (Georgia Tech) from August 15, 2023 to July 31, 2026. The grant will support the development of a "Novel Distributed, Multi-Channel, Topology-Aware Online Monitoring Framework of Massive Spatiotemporal Data" called A-DMIT. This framework aims to advance online threat detection...
Georgia Tech Research Corporation will receive $299,703 under a three-year Project Grant from the National Science Foundation Division of Computing and Communication Foundations' Computer and Information Science and Engineering program (CFDA 47.070). The grant will fund research to develop new techniques in algorithms and complexity analysis to understand how global constraints influence the tractability of sampling and optimization problems on probabilistic graphical models. Specifically, the...
This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $599,972 to Georgia Tech Research Corporation (Georgia Tech Research Corp) to develop a new approach to multifidelity scientific machine learning for engineering design. The research aims to create machine learning models that can effectively leverage both high-fidelity and low-fidelity computational simulations to generate high-accuracy design predictions at low computational cost....
This Project Grant award from the National Science Foundation's (CFDA 47.049 - Mathematical and Physical Sciences) program provides $220,003 to Georgia Tech Research Corporation to conduct research on "Versatile and Scalable Sampling via Geometric Methods, Optimization, and Numerical Analysis." The project aims to develop innovative and versatile sampling algorithms, along with analytical tools, to improve the scalability and performance of sampling techniques for high-dimensional probability distributions. This research has applications in areas such as data science, machine learning, and artificial intelligence, which rely on effective sampling methods to model and simulate complex systems. The award period runs from August 1, 2025 to July 31, 2028.