Project Grant 2533985
- This $450,892 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports the development of novel mathematical and statistical methodologies to establish a foundation for constructing reliable and personalized digital twins for periodontal health. The project aims to integrate principles from statistical learning, topological data analysis, and generative AI to build ensembles of individualized "periodontal digital...
- This National Science Foundation (NSF) Project Grant award under the Mathematical and Physical Sciences program (CFDA 47.049) provides $370,774 to the University of Houston System to develop an innovative framework for learning digital twins of human physiology. The goal is to create personalized, data-enabled digital models that can simulate glucose metabolism and help evaluate new treatments and technologies for type 1 diabetes management, without the risks of real-world trials. The research...
- This Project Grant award, valued at $175,007, was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The award supports the development of a new framework for digital twin modeling of Alzheimer's disease (AD), combining clinical data, biomedical research, and advanced computational methods to enable personalized medicine. The project aims to build a unified modeling framework for...
- The National Science Foundation (NSF) awarded a $1,000,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) federal grant program to The Trustees of the University of Pennsylvania, doing business as Clinical Practices of the University of Pennsylvania. The grant supports the development of an intraoral device that integrates multimodal data from the oral microbiome to predict risk for systemic health issues like neurological problems, heart disease, and...
- This $888,680 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will support collaborative research by the University of Maryland Baltimore County (UMBC) on developing digital twin models and data science techniques for studying neurodegenerative diseases like Alzheimer's, Parkinson's, and multiple sclerosis. The 3-year project aims to advance the theoretical foundations, methodological tools, and algorithmic principles of...
- This $224,994 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of a new framework for digital twin modeling of Alzheimer's disease (AD). The project aims to combine clinical data, biomedical research, and advanced computational methods to create personalized digital twins capable of predicting disease progression and evaluating treatment options for individual patients. The key products or...
- The National Science Foundation awarded $150,000 to Regents of the University of California at Riverside under the Mathematical and Physical Sciences program (CFDA 47.049) from July 1, 2023 to June 30, 2026. The Project Grant funding will support research to develop new statistical methodologies and deep learning techniques for uniformly estimating causal effects of continuous treatments using large observational health data sets. Specifically, the university will design neural network...
- The National Science Foundation (NSF) awarded a $250,000 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to the University of Texas at Austin. The grant, titled "COLLABORATIVE RESEARCH: MATH-DT CLOSING THE GENERALIZATION GAP OF DIGITAL TWINS," aims to develop fundamental theories and robust digital twins that can accurately predict outcomes for complex systems under extreme or unexpected conditions. The project will focus initially on modeling human...
- This Project Grant award from the National Science Foundation (NSF) Mathematical and Physical Sciences program (CFDA 47.049) provides $269,979 to the Santa Fe Institute of Science to conduct collaborative research on developing robust digital twin models that can accurately predict the behavior of complex systems under unexpected conditions. The key objectives are to: Investigate the generalization abilities of digital twins by combining mathematical tools from nonlinear dynamics and machine...
- This $200,000 Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) aims to develop the mathematical and statistical foundations for a Digital Twin (DT) system to enhance neurophysiological modeling and uncertainty quantification for individuals with Autism Spectrum Disorder (ASD). The key products and services to be delivered include: Computational models based on Conditional Variational Auto-Encoders (CVAE) and longitudinal CVAE to analyze brain...
The National Science Foundation (NSF) awarded a $300,011 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) program to the Regents of the University of California at Riverside. The grant, titled "Collaborative Research: FDT-BioTech: Digital Twins with Statistical Topological Learning of Periodontal Diseases", aims to develop novel mathematical and statistical methodologies to establish an AI-driven framework for constructing reliable and personalized digital twins (DTs) for periodontal health. By integrating principles from statistical learning, topological data analysis, and generative AI, the project seeks to build ensembles of individualized "periodontal digital siblings" that capture patient variability and uncertainty, offering more precise representation of individual health profiles. This interdisciplinary effort bridges mathematics, statistics, machine learning, dental science, and healthcare, with the goal of transforming the prevention and treatment of periodontal disease through personalized, data-driven care.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $300.0k | 8/20/25 |