Project Grant 2310288
Award Date
7/1/23
Completion Date
6/30/26
Dollars Obligated
$150K
Federal Agency
Division of Mathematical Sciences
Federal Grant Program
47.049
Assistance Type
Project Grant
Place of Performance
Riverside, CA 92521, USA
Similar Awards
This Project Grant award, valued at $250,000.00, was granted by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program. The award will support a research project titled "Deep Learning for Survival Analysis, Causal Inference, and Conformal Inference" at the University of California, Davis. The key objectives of this 3-year project are to: 1) develop new hypothesis testing procedures for deploying deep learning methods in survival...
The National Science Foundation awarded The Regents of the University of California $330,000 under the Mathematical and Physical Sciences program (CFDA 47.049) to advance theory and methodology for tree-based algorithms in high dimensions from July 2022 to June 2025. The project will analyze the generalization performance of tree-based algorithms on regression models to better understand their inductive bias for different data structures. It will also study a new framework for obtaining...
This $175,000 federal Project Grant award from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) supports the development of new statistical and computational methods to enhance the reliability of data analysis in modern, large-scale datasets. The three-year project (7/1/2025 - 6/30/2028) at the University of California, Davis focuses on: (1) analyzing the robustness of manifold and deep learning algorithms for high-dimensional, noisy, and nonlinear data;...
This National Science Foundation Project Grant of $220,000 supports research into statistical modeling methods for large, complex datasets. Funded under the Mathematical and Physical Sciences program (CFDA 47.049), the University of California, San Francisco will develop new Bayesian regression techniques using random data compression matrices. These approaches aim to enable efficient, scalable inference and prediction from high-dimensional biomedical data sources like brain imaging, genetics,...
The National Science Foundation Division of Mathematical Sciences awarded $299,997 under the Mathematical and Physical Sciences federal grant program (CFDA 47.049) to the University of California, Davis for a three-year project grant completing June 2025. The award will support research involving the development of new statistical testing methods and deep learning techniques for functional data analysis. Specifically, the university will conduct research projects to create a general framework...
This $329,020 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports the development of new analytical tools for making informed decisions based on complex, high-dimensional unstructured data types such as text, images, and gene expressions. The key research objectives are to: 1) develop novel causal inference methods for high-dimensional data, 2) design probabilistic...
This three-year $200,000 Project Grant from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) supports research at the University of California, Irvine to develop new statistical methods and computational tools for analyzing complex, intensive longitudinal biomedical data. Specifically, the grantee will study heterogeneous epigenetic effects of post-traumatic stress disorder using high-dimensional DNA methylation modeling. They will also develop optimal...
This $200,000 project grant was awarded by the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program to the University of Delaware. The grant will support the development of new nonparametric learning methods for high-dimensional survival data analysis, with applications in causal inference and sequential decision-making problems. The research aims to advance the state-of-the-art in areas like medical risk factor discovery, personalized treatment...
This $169,999 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports collaborative research at the University of California, Davis (UC Davis) to advance innovative nonparametric data analysis techniques. The project aims to conduct comprehensive statistical and computational analyses to push the boundaries of modern nonparametric statistical inference, with potential applications in areas like nonparametric latent...
This National Science Foundation Project Grant of $133,850 supports research at Clemson University under the Mathematical and Physical Sciences program (CFDA 47.049) from August 15, 2022 through July 31, 2025. The award will fund the development of statistical analysis frameworks to incorporate abundant data features, including medical images, genetic information, and other patient characteristics, into precision medicine decision-making tools. Specifically, the researchers will adapt...