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,...
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 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 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 Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $100,000 to Arizona State University (ASU) to establish the Industry-University Cooperative Research Center for Digital Twins in Manufacturing (IUCRC-DTM). The IUCRC-DTM will conduct fundamental research to advance digital twin technology for manufacturing applications, such as developing a reusable digital twin framework, improving key digital twin components, and creating tools...
This federal Project Grant award of $1,500,000.00 by the Air Force Research Laboratory (CFDA 12.800 - Air Force Defense Research Sciences Program) supports research on the Mathematics of Digital Twins. Key products and services to be delivered under this award include: Development of mathematical algorithms and computational methods for uncertainty quantification, parameter estimation, and data assimilation for digital twin prototyping (The Ohio State University) Creation of a framework for...
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...
This $199,066 Project Grant awarded by the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports research to automate the creation of digital twins for manufacturing systems. The key innovations include: Developing a dataset of manufacturing shop floor videos with annotated manufacturing elements to train autonomous digital twin instantiation methods. Creating a neural radiance field (NeRF) model to reconstruct the shop environment as a high-fidelity 3D model....
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 National Science Foundation Project Grant of $283,099 will support the development of new stochastic optimization methods to calibrate digital twins using large datasets. Awarded under the Engineering program (CFDA 47.041), the grant will fund research at the University of Michigan from January 2023 through December 2025. Specifically, the university researchers will develop computational approaches using statistical theories to guide simulation experiments and identify optimal subsets of...