This Project Grant award for $117,910 from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) aims to develop new statistical estimation methods and algorithms that can efficiently process complex, high-dimensional datasets. The research will focus on three key areas: (1) providing rigorous theoretical guarantees for the performance of high-dimensional statistical estimation techniques, (2) establishing computational limits and efficiencies for modern...
This three-year, $260,000 Project Grant from the National Science Foundation's Division of Mathematical Sciences, under the Mathematical and Physical Sciences program (CFDA 47.049), will fund research towards designing optimal statistical learning procedures through precise medium-dimensional asymptotic analysis. The grantee, Columbia University, will develop a novel analytical framework to quantitatively characterize the performance of diverse learning algorithms and provide guidance on...
This Project Grant from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) provides $193,202 to Columbia University from August 15, 2022 through July 31, 2025. The funding will support research investigating long-time behavior and large population limits of stochastic processes with random times. Specifically, the university will develop mathematical and computational tools to analyze complex interacting systems, with a focus on stochastic models involving...
Columbia University was awarded a $120,929 project grant from the National Science Foundation Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049). The grant will fund collaborative research on statistical inference methods for high-dimensional spatial-temporal process models from July 1, 2021 to June 30, 2024. As part of the Mathematical and Physical Sciences program's goal of advancing scientific knowledge and understanding of national...
This Project Grant award of $160,000.00 from the National Science Foundation (NSF) Division of Mathematical Sciences, under the Mathematical and Physical Sciences (CFDA 47.049) grant program, will support a "Collaborative Research: Partial Priors, Regularization, and Valid & Efficient Probabilistic Structure Learning" project. The research aims to develop new statistical methods and frameworks for reliable uncertainty quantification in high-dimensional structure learning problems...
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...
This $155,372 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program will fund research to develop advanced statistical methods for extracting insights from high-dimensional, high-frequency "big data." The University of Illinois, Chicago, as the prime awardee, will focus on four key areas: 1) advancing contiguity theory to enable more robust statistical analysis of noisy, high-frequency data; 2) exploring time-varying...
The National Science Foundation Division of Mathematical Sciences awarded Columbia University a $170,000 Project Grant under the Mathematical and Physical Sciences federal grant program (CFDA 47.049) for work on "MEAN-FIELD MODELS IN STATISTICS" from July 1, 2021 to June 30, 2024. The grant aims to promote progress in the mathematical and physical sciences by increasing scientific knowledge and enhancing understanding of major problems through Columbia University's work on mean-field...
This $350,000 federal Project Grant was awarded by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program. The goal of the research is to develop accurate mathematical models and computer simulations for studying non-equilibrium systems with memory effects, such as those found in biosystems, plasma evolution, and solid-state nanostructures. The Principal Investigator will focus on analytical and numerical approaches to statistical transport...
This $240,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports research by The Trustees of Columbia University in the City of New York to develop computationally efficient algorithms for approximating machine learning (ML) model outputs when removing subsets of training data. The research aims to advance scientific understanding of AI, improve the robustness of decision-making systems, and contribute to the...