The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $331,902 Project Grant to the Trustees of Boston University on August 15, 2023 under the Mathematical and Physical Sciences program (CFDA 47.049). The purpose of this 3-year grant is to develop rigorous mathematical analysis and theory for the training algorithms used in neural network models across various machine learning applications. The research will leverage stochastic analysis and weak convergence theory...
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...
The Trustees of Boston University will use a $638,578 project grant from the National Science Foundation to develop deep learning models for microbial image analysis and time-series predictions under the Biological Sciences program. The three-year award, issued on January 1, 2022 and set to conclude December 31, 2024, will support efforts to promote progress in the biological sciences through increased understanding of major problems confronting the nation. Specifically, the university will...
This $888,680 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports a collaborative research effort at the University of Maryland Baltimore County (UMBC) to develop digital twin models and techniques for studying neurodegenerative diseases like Alzheimer's, Parkinson's, and multiple sclerosis. The 3-year project, running from September 2024 to August 2027, will address challenges in manifold learning, causal pathway...
This $200,000 Project Grant award from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) aims to develop novel feature selection techniques for supervised and unsupervised machine learning models. The research will focus on the "knockoff method" for identifying key predictive features while controlling false discoveries, incorporating microbiome data structures, handling missing values, and...
The National Science Foundation (NSF) awarded a $519,526 Project Grant under its Mathematical and Physical Sciences program (CFDA 47.049) to Texas Tech University System, a Hispanic Serving Institution, to develop new mathematical models and computational software for studying how modifiable risk factors like diet, exercise, and sleep impact the progression of Alzheimer's disease. The project aims to: 1) devise novel network dynamical systems models to describe the evolution of Alzheimer's...
This National Science Foundation project grant of $260,000 supports research at the University of North Carolina at Chapel Hill to develop statistical analysis frameworks for precision medicine incorporating abundant data features. Funded under the Mathematical and Physical Sciences program (CFDA 47.049), the three-year award running from August 2022 to July 2025 will adapt semi-parametric and reinforcement learning methods to precision medicine scenarios involving medical images, genetic...
The Trustees of Boston University were awarded a two-year, $299,995 Project Grant from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) to support the "EAGER: ADAPT: AI Guided Design and Synthesis of Semiconducting Molecules" project. Through this funding, Boston University will utilize artificial intelligence to guide the design and synthesis of novel semiconducting molecules with desirable properties for electronic and optoelectronic...
This National Science Foundation (NSF) Division of Mathematical Sciences award under the Mathematical and Physical Sciences (CFDA 47.049) program provides $131,615 to the University of Illinois to develop novel Bayesian joint models for analyzing complex, high-dimensional health data. The research aims to improve methods for utilizing information from longitudinal measurements, such as clinical data and biomarkers, to associate with and predict time-to-event outcomes like disease progression...
The National Science Foundation (NSF) awarded a $498,229 Project Grant under its Mathematical and Physical Sciences program (CFDA 47.049) to Yale University. The grant will fund research to develop new mathematical and machine learning techniques for analyzing complex, high-dimensional biomedical data such as single-cell sequencing and gene regulatory networks. Key research thrusts include creating data geometric features and neural network models to characterize point cloud data, preserving...