Haofeng Zhang is a Ph.D. candidate at the Department of Industrial Engineering and Operations Research at Columbia University. His primary research interests are in data-driven prediction and decision-making methodologies, particularly: 1) Decision-making under uncertainty: data-driven stochastic optimization, multi-armed and contextual bandit problems, black-box and Bayesian optimization. 2) Uncertainty quantification and reduction, including simulation-based approaches, calibration, distributional robustness and shift.
