Projects:
1. Title: AEOLUS: Advances in Experimental Design, Optimal Control, and Learning for Uncertain Complex Systems
Sponsor: DOE ASCR MMICCs program
Lead PIs: Omar Ghattas, Karen Willcox
Co-PIs: Francis Alexander (Brookhaven), George Biros, Ed Dougherty (TAMU), Max Gunburger, Youssef Marzouk (MIT), Robert Moser, J. Tinsley Oden, John Turner (ORNL), Clayton Webster.
Website: https://aeolus.oden.utexas.edu
2. Title: Learning Optimal Aerodynamic Designs
Sponsor: ARPA-E
PI: Omar Ghattas
Co-PIs: Joaquim Martins (Michigan), Karen Willcox
Website: https://arpa-e.energy.gov/technologies/projects/learning-optimal-aerodynamic-designs
3. Title: Scalable and Efficient Approximation of Hessians for Seismic Inverse Problems
Sponsor: Total E&P
PI: Omar Ghattas
4. Title: Hybrid Discretizations of Wave Equations in Petroleum Exploration
Sponsor: KAUST
PI: Omar Ghattas
5. Title: Finding Optimum Magnetic Fields with Hidden Symmetries
Sponsor: Simons Foundation
PI: Omar Ghattas (collaboration with Princeton, NYU, Cornell, Columbia, Wisconsin, Australian National University, Max Planck Institute for Plasma Physics, Maryland, Warwick, Colorado–Boulder)
Website: https://hiddensymmetries.princeton.edu
6. Title: Scalable Computational Methods for Large-scale PDE-constrained Stochastic Optimization Under High-dimensional Uncertainty Sponsor: NSF DMS
PI: Peng Chen
Co-PI: Omar Ghattas
7. Title: Computation for the Endless Frontier/ Operations & Maintenance for the Endless Frontier
Sponsor: NSF OAC
PI: Dan Stanzione
Co-PIs: Omar Ghattas, Tommy Minyard, D.K. Panda (Ohio State), and John West
Website: https://frontera-portal.tacc.utexas.edu/
8. Title: Preliminary Design Planning for the Leadership-Class Computing Facility
Sponsor: NSF OAC
PI: Dan Stanzione
Co-PIs: Omar Ghattas, John West
9. Title: RISE of the Machines: Robust, Interpretable, Scalable, Efficient Decision Support
Sponsor: DOE ASCR
Lead PI: Karen Willcox
Co-PIs: Omar Ghattas, John Jakeman (Sandia), Lars Ruthetto (Emory), Bart van Bloemen Waanders (Sandia)
10. Title: Machine Learning for Physics-based Systems: Optimal Approximations, Architectures, and Training
Sponsor: DOD/MURI
PI: Karen Willcox
Co-PIs: Omar Ghattas, Jorge Nocedal (Northwestern), Hayden Schaeffer (CMU), Steve Wright (Wisconsin)
