Speaker: Prof. Dr. Güzin Bayraksan (Ohio State University)
Title: Integrating Stochastic Optimization and Machine Learning Using Residuals
Date: June 3,2025
Time: 10:00
Place: EA409
We present data-driven approaches that integrate machine learning with stochastic optimization by using residuals from the learning models. Given a new covariate/contextual observation, the goal is to choose a decision that minimizes the expected objective function conditioned on this observation. We first describe a Sample Average Approximation (SAA) approach for approximating this problem and examine its theoretical properties. We then present its application to a unit commitment problem in power systems with renewable energy generation using real-world data. Finally, we discuss several extensions such as the Distributionally Robust Optimization (DRO) variants in limited-data regime and under decision-dependent uncertainty with applications in energy and transportation systems.
Bio:
Güzin Bayraksan is a Professor and Associate Chair for Research in the Integrated Systems Engineering Department and an affiliated faculty member of the Sustainability Institute and the Translational Data Analytics Institute at the Ohio State University. Her research interests are in optimization under uncertainty, particularly stochastic and distributionally robust optimization, using data-driven, contextual, and Monte Carlo simulation-based methods. She applies these models and methods to solve problems of critical societal interest in water, energy, and transportation systems. Her papers have appeared in top journals such as Mathematical Programming, SIAM Journal on Optimization and Operations Research, and her research has been supported by multiple grants from the National Science Foundation (NSF) and the Department of Energy (DoE). She is the recipient of INFORMS ENRE Best Publication Award in Environment and Sustainability, Lumley Research Award (OSU), NSF CAREER award, Five Star Faculty Award (UA), and the INFORMS best case study award. She served as the Chair of Stochastic Programming Society (SPS) (2019-2023), the Vice Chair of Optimization under Uncertainty of INFORMS Optimization Society, and the President of the INFORMS Forum on Women in Operations Research and Management Science.