Michael Jong Kim

Michael Jong Kim is an Associate Professor in the Operations and Logistics Division at The University of British Columbia Sauder School of Business. His research focuses on Dynamic Programming, Statistical Learning, Robust Optimization, and the Exploration vs Exploitation Trade-offs. He has published in leading journals such as Operations Research, Management Science, and Mathematics of Operations Research. His work includes topics like Bayesian Inventory Control, Learning Manipulation through Information Dissemination, and Variance Regularization in Sequential Bayesian Optimization. Kim teaches courses such as Descriptive and Predictive Business Analytics and Advanced Predictive Business Analytics at the MBA level.