NSF-Simons AI Institute for Cosmic Origins

CosmicAI develops transformative AI methods to meet pressing astronomical challenges and tackle outstanding questions about our cosmic origins. Research spans four fundamental AI themes: trustworthiness, efficiency, interpretability, and robustness.

Led out of the Oden Institute, CosmicAI aims to serve as a nexus of collaboration to increase the accessibility of astronomy and AI data and methods through open-source AI-powered tools, data sharing, and AI educational initiatives.

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Digital Twins

The Oden Institute is leading research to advance the science and impact of digital twins.

Our work is establishing digital twin mathematical and computational foundations, including scalable methods for data assimilation, inverse problems, decision-making and control, and new approaches to address digital twin verification, validation and uncertainty quantification. Our work is advancing digital twin applications across science, engineering and medicine.

Selected Projects

1. M2dt: Multifaceted Mathematics for Predictive Digital Twins

   A U.S. Department of Energy Mathematical Multifaceted Integrated Capability Center

   PIs: Ghattas, Willcox, Biros, Heimbach, Lu, Ward

   Collaborating Institutions: Massachusetts Institute of Technology, Sandia National Laboratories, Brookhaven National Laboratory, Argonne National Laboratory

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2. Mathematical and Computational Foundations for Predictive Digital Twins

   U.S. Air Force Office of Scientific Research Multidisciplinary University Research Initiative (MURI) Program

   PIs: Willcox, Ghattas

   Collaborating Institutions: Stanford University, NYU Courant Institute, University of Chicago, University of Tennessee Knoxville

3. Digital Twin Enabled Autonomous Control for On-Orbit Spacecraft Servicing

   U.S. Space Force Space University Research Initiative (SURI) Program

   PI: Willcox

   Collaborating Institutions: UC Santa Cruz, University of Michigan

4. MuSiKAL: Multiphysics Simulations and Knowledge discovery through AI/ML technologies

   U.S. Department of Energy, Advanced Scientific Computing Research (ASCR) Program

   PIs: Dawson, Bui, Yang, Niyogi, Scanlon

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5. A digital twin framework for developing and analyzing virtual patient cohorts to enable virtual clinical trials

   NSF/NIH/FDA Foundations for Digital Twins as Catalyzers of Biomedical Technological Innovation (FDT-Biotech)

   PIs: Hormuth, Chaudhuri, Kileel, Willcox, Yankeelov