Project Grant 2529292
- 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 federal Project Grant award for $444,202, provided by the National Science Foundation's (CFDA 47.049) Mathematical and Physical Sciences program, supports research at the University of Utah to develop a novel mathematical and computational framework for dramatically accelerating the calibration and updating of digital twin models. Digital twins are virtual representations of physical systems that enable real-time simulation, monitoring, and prediction of their real-world counterparts,...
- 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 $256,000 National Science Foundation Engineering Directorate Project Grant supports the development of a digital twin composition method by Diamond Age Technology LLC. The awardee will develop techniques to efficiently combine disparate data sources describing industrial process facilities into a single digital representation with sub-centimeter accuracy. This digital twin can then be projected into spatial computing environments like virtual and augmented reality. The goal is to encode...
- 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...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) federal grant award provides $174,980 to the Rochester Institute of Technology (RIT) to develop techniques and a framework for enabling "live 3D digital twins" - real-time digital representations of 3D physical objects. The project aims to create adaptive digital twin pipelines that can maintain low latency and high accuracy across varying network and compute resources, with applications...
- 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 from the National Science Foundation (NSF) under the Engineering program (CFDA 47.041) provides $199,066 in funding to Miami University to support research on automating the creation of digital twins for manufacturing systems. The research aims to leverage computer vision and deep learning techniques to reduce the manual effort required to build digital twins, while improving their accuracy and interoperability. Key innovations include developing a dataset of...
- The National Science Foundation (NSF) awarded a $429,040 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) federal grant program to The University of Texas at San Antonio (UTSA). The grant funds a collaborative research project titled "COMPUTATIONALLY EFFICIENT HYPERCOMPLEX VARIABLE-BASED SENSITIVITY METHODS FOR RAPID DIGITAL TWIN MODEL UPDATING." The project aims to develop a new mathematical and computational framework to dramatically accelerate the process...
- 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 $500,005.00 Project Grant award from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) aims to develop innovative methodologies for quantifying and controlling rare events in complex systems using digital twins. The project, titled "RAREDT: Rare Event Quantification and Control in Digital Twins," will create digital twin models that explicitly incorporate rare event quantification and control to enhance safety and resilience in areas such as transportation, infrastructure planning, and disaster response. The research combines advances in mathematics, statistics, and algorithm development to enable AI-enabled digital twin technologies that are reliable and robust in extreme scenarios. The award to the University of Pennsylvania will fund this work from September 15, 2025 through August 31, 2028, and includes an educational component to offer new courses, workshops, and outreach activities.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $500.0k | 8/5/25 |