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Luhao Zhang is an Assistant Professor in the Department of Applied Mathematics and Statistics at Johns Hopkins University. His research focuses on optimal decision-making in stochastic and uncertain environments, emphasizing the modeling of quantitative aspects. He has advanced new tractable methodologies in data-driven distributionally robust optimization, personalized decision-making, and dynamic information acquisition. His work lies at the intersection of decision-making under uncertainty, stochastic robust optimization, machine learning, continuous-time reinforcement learning, and algorithmic fairness. He received his bachelor's degree in applied mathematics with honors from Xi’an Jiaotong University, China, in 2018, and his PhD in mathematics from the University of Texas at Austin in 2023. He is currently a postdoctoral research scientist in the Department of Industrial Engineering and Operations Research at Columbia University.
Department of Pathology - PhD in Pathobiology. GRE is not required.