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 $293,784 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports fundamental and applied research on fluctuating systems, random environments, and stochastic algorithms. The research aims to improve understanding and exploitation of randomness across diverse settings, including materials science, fluid dynamics, and machine learning. Key areas of focus include stochastic homogenization, stochastic partial...
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...
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 (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...
This $600,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research at North Carolina State University to explore advanced sampling and optimization techniques for decentralized machine learning. The key objectives are to: Enhance the sampling efficiency of interacting nonlinear Markov chains through adaptive spatio-temporal repellency among multiple "self-repellent random walks",...
This Project Grant award from the National Science Foundation's (NSF) Division of Mathematical Sciences program (CFDA 47.049) will fund research to develop scalable subsampling algorithms for statistical inference on large-scale networks. The $150,000 grant, awarded on August 15, 2024, will be used to investigate theoretical properties of these subsampling methods and apply them to network data from social and natural sciences, including the study of mindfulness-based therapies for disorders...
This federal Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $600,000 in funding to Northeastern University from January 1, 2025 to December 31, 2027. The primary objective of this research project is to advance the understanding of randomness in computation, with the goal of improving the performance and security of everyday technology. Key areas of investigation include pseudorandom...
This $349,993 federal Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program will advance the methodology and practical implementation of adaptive experiments. The 3-year project, which begins on September 1, 2024, will develop new statistical methods for sample size calculations and optimal treatment assignment in adaptive settings, establish a comprehensive framework to guide applied researchers in designing adaptive...
The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $200,000 Project Grant to The University Corporation, a non-profit organization located in Northridge, CA. The grant, funded under the NSF's Mathematical and Physical Sciences program (CFDA 47.049), focuses on developing new statistical modeling and data resampling methods to address challenges posed by incomplete, missing, and fragmented observations in large datasets. Key objectives include: Advancing...