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...
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 three-year, $359,998 Project Grant from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) will fund the development of statistical and computational tools for analyzing high-dimensional heterogeneous data. Specifically, the awardee, Columbia University, will create new methodologies for clustering and identifying latent structures in complex data involving multiple attributes and relationships.
The research has three parts. The first will develop...
Columbia University has been awarded a three-year $300,000 Project Grant from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) to develop nonparametric testing methods for multivariate and Hilbert space-valued data. Specifically, the university will create a distribution-free statistical inference framework for multivariate data that generalizes univariate rank-based methods. Researchers will also study the asymptotic relative efficiency of...
This $100,011 federal Project Grant award was provided by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program. The award supports research conducted by The Trustees of Columbia University in the City of New York on stochastic growth models, mathematical structures called line ensembles, and their applications in areas such as magnetization, traffic, and protein synthesis. The research aims to expand the understanding of these mathematical...
The Trustees of Columbia University in the City of New York (Columbia University) was awarded a $329,639 Project Grant from the National Science Foundation Division of Mathematical Sciences under the Mathematical and Physical Sciences federal grant program (CFDA 47.049).
The grant funds the development of novel statistical methodology to model, analyze, and predict the evolution of geometric and topological features in random objects over time. Columbia University researchers will establish...
The Trustees of Columbia University in the City of New York (Columbia University) was awarded a $394,840 Project Grant from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049). The grant will fund research into advancing the mathematical and algorithmic development of nonlocal models involving finite-range nonlocal interactions through July 2026. Specifically, Columbia University will focus on analytical and algorithmic solutions for nonlocal...
This $289,999 National Science Foundation project grant, awarded under the Mathematical and Physical Sciences program (CFDA 47.049), will fund the development of improved statistical methods, algorithms, and theory for estimation and inference with high-dimensional data at Rutgers, The State University from July 2022 through June 2025. Key products include new statistical methods for regularized estimation, de-biased statistical inference including confidence intervals and regions, and...
The National Science Foundation (NSF) awarded a 3-year, $250,015 Project Grant under its Mathematical and Physical Sciences program (CFDA 47.049) to The Trustees of Columbia University in the City of New York. The primary goal of this collaborative research project is to develop advanced statistical and machine learning techniques to forecast and analyze high-dimensional extreme events, such as extreme climate conditions and social phenomena. Key research thrusts include: 1) Learning the...
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...
This $117,910 federal Project Grant was awarded by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program to The Trustees of Columbia University in the City of New York. The grant funds research to address fundamental challenges in high-dimensional statistical estimation and data analysis, with the goal of developing computationally efficient methods that can perform close to theoretical limits. Key focus areas include: (1) providing theoretical guarantees for estimation performance in high-dimensional linear models; (2) establishing computational limits for modern statistical procedures under complex modeling assumptions; and (3) leveraging high-dimensional estimation techniques to design new, efficient algorithms for wireless communication. The research aims to increase the computational efficiency of statistical algorithms, improve estimation quality from limited data, and create new applications of these methods in areas like wireless communications. In addition to the research activities, the grant includes initiatives to support and develop the academic portfolios of underrepresented undergraduate students in statistics and data science in the New York tri-state area.