Project Grant 2439054

Award Date 8/1/25
Completion Date 7/31/30
Dollars Obligated $597K
Federal Grant Program
47.049
Assistance Type
Project Grant
Place of Performance
Moscow, ID 83844, USA
Similar Awards
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 $455,825 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) was granted to Iowa State University of Science and Technology to develop a personalized digital twin technology for monitoring and understanding cardiovascular aging. The project aims to integrate data from wearable devices, echocardiographic measurements, and advanced cardiovascular modeling to enhance the monitoring and early detection of...
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...
The National Science Foundation (NSF) Division of Chemical, Bioengineering, Environmental, and Transport Systems awarded a $410,527 CAREER grant to the University of Texas at Dallas for the project "A Systems Approach to Create Multiplexed Microfluidics to Study Human Immune Cell Dynamics." The 5-year project seeks to develop validated models of human inflammation in tissue microenvironments using microfluidic devices, mathematical modeling, and computational simulations. The goal is...
This Federal Project Grant award, provided by the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049), supports the development of a first-principles informed, data-enabled predictive digital twin framework for human physiology. The $432,000 award to Arizona State University, a Hispanic-serving institution, will advance techniques for integrating real-world data into physics-based models to create personalized digital representations of human metabolic...
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 $200,000 Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CFDA 47.070) program will fund the development of advanced computational methods to create high-fidelity, fast-running digital twins of patient hearts and cardiovascular medical devices. The project aims to deliver: 1) novel machine learning algorithms for accurate digital twin geometry reconstruction from 3D medical images, 2) an efficient inverse method to identify in vivo...
This Project Grant award from the National Science Foundation's (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049) aims to develop a personalized digital twin technology that will enhance the monitoring and understanding of cardiovascular aging. The $250,000 award to Lehigh University will integrate data from wearable devices, echocardiographic measurements, and advanced cardiovascular modeling to create a physics-based...
This Project Grant award, funded by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program, supports fundamental research to improve the generalization capabilities of digital twin models for complex systems. The $269,187 grant will enable researchers at Smith College to develop hybrid digital twin architectures that combine physics-based and domain-agnostic components, allowing for improved predictive performance across a range of conditions,...
This four-year Project Grant from the National Science Foundation's Division of Civil, Mechanical, and Manufacturing Innovation provides $399,585 to the University of Florida for collaborative research titled "A Causal AI Digital Twin Framework to Transform Intensive Care Delivery." The award's stated purpose is to support investigator-initiated research and education under the Computer and Information Science and Engineering program (CFDA 47.070). Specifically, the University of...

This National Science Foundation (NSF) CAREER award under the Mathematical and Physical Sciences program (CFDA 47.049) provides $597,138 to the University of Idaho to initiate the construction of a generic "immune digital twin" - a software replica of the immune system that can provide insights into biology, health, and disease. The project aims to address two key questions: 1) What level of mathematical abstraction and granularity is required to represent an immune digital twin? and 2) How can diverse data types be integrated to calibrate and validate its components? To achieve this, the project will develop the mathematical foundations for immune digital twins, integrate multi-scale data to calibrate these models, and create a blueprint for an immune cell digital twin. This research will be complemented by the development of summer research programs and educational courses to introduce undergraduate students to digital twin science. The overarching goal is to advance computational methods that can predict immune responses in a virtual environment, contributing to national prosperity.

Generated 8/5/25, 4:13 AM