The ISE Department congratulates Frank for this formidable achievement. The Lagrange Prize in Continuous Optimization is a major award MOS and SIAM, which are irrefutably two of the most prestigious societies of optimization and applied mathematics. It has been awarded since 2009, and among past awardees there are famous mathematicians and optimizers such as Emmanuel J. Candès, Roger Fletcher, Jean-Bernard Lasserre, and Francis Bach.
The selection committee awarded Frank E. Curtis and his co-authors Léon Bottou and Jorge Nocedal for the paper L. Bottou, F. E. Curtis, and J. Nocedal, Optimization methods for large-scale machine learning, SIAM Review, 60 (2018) 223–311. Their work provides a foundational and insightful review of optimization methods for large-scale machine learning, including a new perspective for the simultaneous consideration of noise reduction and ill-conditioning and the foundations and analysis of second-order stochastic optimization methods for machine-learning.
The selection committee for the 2021 award consisted of Sven Leyffer (Chair), Argonne National Laboratory; Xiaojun Chen, The Hong Kong Polytechnic University; Etienne de Klerk, Tilburg University; and Philip Gill, University of California, San Diego. The prize will be awarded at the 2021 SIAM Annual Meeting, scheduled to be held in a virtual format on July 19-23, 2021.
Frank E. Curtis is an Associate Professor and Director of Graduate Studies in the ISE Department. His research spans theory, algorithm design, and numerical computation in the field of continuous mathematical optimization. Frank is also a recipient of the ICS Prize awarded by the INFORMS Computing Society. His research has been supported by the U.S. Department of Energy (including an Early Career award), National Science Foundation, and Office of Naval Research.