Dr. Luis Nunes Vicente
ISE Department
Lehigh University
Friday, November 3, 2023
Tickle 500 1:50-2:40pm
Abstract: Our work aims to develop state-of-the-art stochastic methodologies and rigorous theoretical analyses to expand the knowledge of multi-level multi-objective optimization in many directions. These methods address relevant problems arising in machine learning, cybersecurity, and defense, such as adversarial learning, network interdiction, and power network defense. Stochastic gradient methods are well studied for single-level problems, and there has been some recent advance for bilevel problems or multi-objective single-level problems, but many application problems exhibit features such as conflicting objectives at different levels, more than two levels, or discrete variables, which have never been studied from a stochastic approximation view point. Our work aims to fill this gap by leveraging ideas from stochastic bilevel and multi-objective optimization to extend the algorithmic framework and convergence analysis beyond classic stochastic gradient methods. We investigate several stochastic problems such as bilevel problems with constraints at the lower level, bilevel problems with multiple objective functions in at least one of the levels, trilevel optimization problems, and bilevel problems with some of the variables restricted to be integers.
Bio: Luis Nunes Vicente is the Timothy J. Wilmott ’80 Endowed Faculty Professor and Chair of Lehigh University’s Department of Industrial and Systems Engineering (ISE), effective August 1, 2018, after a career as a faculty member in the Department of Mathematics of the University of Coimbra. His research interests include Continuous Optimization, Computational Science and Engineering, and Machine Learning and Data Science.
He obtained his PhD from Rice University in 1996, under a Fulbright scholarship, receiving from Rice the Ralph Budd Thesis Award. He was one of the three finalists of the 94-96 A. W. Tucker Prize of the Mathematical Optimization Society. In 2015, he was awarded the Lagrange Prize of SIAM (Society for Industrial and Applied Mathematics) and MOS.
He held visiting positions at IBM Research, NYU, Rice, CERFACS, and Rome/Sapienza. He has served on numerous editorial boards, including SIAM Journal on Optimization and Mathematical Programming.
Recently, he was elected chair of the SIAM Activity Group on Optimization for 2023-2025 and chair of ACORD in 2023 (the Association of Chairs of OR Departments at INFORMS).