Hao Zhang

Hao Zhang is an Associate Professor in the Operations and Logistics Division at the Sauder School of Business, University of British Columbia. He holds a Ph.D. from Stanford University. His research focuses on stochastic games, dynamic principal-agent problems, information asymmetry in operations management, and applications of machine learning in operations. He teaches courses such as Analyzing and Modelling Uncertainty and Advanced Topics in Stochastic Models (PhD).

Key research themes include partially observable Markov decision processes (POMDPs), reinforcement learning, supply chain dynamics, and healthcare management. Recent work addresses analytical solutions for machine maintenance under partial observability and dynamic learning frameworks using basis weight vectors.

Zhang's publications span prestigious journals like Management Science and Operations Research. His work combines theoretical rigor with practical applications in inventory management, revenue optimization, and supply chain coordination.