Zhengyuan Zhou

  I'm an assistant professor in Department of Technology, Operations, and Statistics at Stern School of Business, New York University. I'm also associated faculty at Department of Computer Science and Engineering, Tandon School of Engineering and affiliated faculty at NYU Center for Data Science.

Before joining NYU Stern, I obtained my Ph.D. from Department of Electrical Engineering at Stanford University in summer 2019, advised by Professor Nick Bambos and Professor Peter Glynn. During the year 2019-2020, I was gratefully supported by the IBM Goldstine fellowship and also a visiting assistant professor at NYU Stern.

My research interests lie at the intersection of machine learning, sequential decision making, optimization and stochastic systems. I'm broadly interested in developing sample-efficient and computationally efficient policy learning algorithms for data-driven decision making problems. Some of my recent research projects include distributionally robust policy learning, learning to adaptively bid in first-price auctions, efficient policy learning with limited adaptation, multi-agent cooperative and game-theoretical learning, offline policy learning using adaptively collected data.

Email : zzhou@stern.nyu.edu

Research Interests

  • Contextual bandits

  • Reinforcement learning

  • Stochastic optimization

  • Learning in games

  • Revenue management

  • Inventory control

  • Data-driven decision making