Antil Studying Compression & Randomization For Extreme-Scale Training & Optimization (CREST Opt)

Harbir Antil, Professor, Mathematical Sciences,and Director, Center for Mathematics and Artificial Intelligence (CMAI),received funding for a project in which he and his collaborators will develop novel, rapidly converging algorithms for non-smooth optimization problems, including constrained, bi-level, and risk-averse problems.  

To ensure that their methods are computationally feasible for dynamic problems, the researchers will augment them with randomized preconditioning and compression techniques.  

Regarding the importance of this project, Antil said, "If successful our proposed work will enable scalable automated design, data analysis and optimization of highly nonlinear dynamical systems with uncertainty. In total, the technologies developed in this project will enable numerical optimization for use in some of the most challenging problems across the DoD research portfolio." 

Antil received $300,000 from the U.S. Department of the Air Force for this project. Funding began in April 2022 and will end in April 2025.