About.

Min-hwan Oh is an Associate Professor in the Graduate School of Data Science at Seoul National University. His research focuses on sequential decision-making under uncertainty, reinforcement learning, bandit algorithms, optimization, statistical machine learning, and their various applications. He received his Ph.D. in Operations Research with a specialization in Data Science from Columbia University under the supervision of Garud Iyengar and Assaf Zeevi. Before his Ph.D., he graduated summa cum laude with a B.A. in Mathematics and Statistics from Columbia University. His doctoral thesis was recognized as a finalist for the INFORMS George B. Dantzig Dissertation Award and the Applied Probability Society’s Best Student Paper Award.

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