Learning Algorithms

  • Reinforcement learning with provable results.
  • Bayesian (simulation) optimization.
  • Online resourcing allocation and matching.

Complex Systems

  • Multimodal transportation systems.
  • Transportation policy for automated vehicles.
  • Data-driven supply chain management.

Game Theory

  • Incentive contracts and dynamic games.
  • Mean-field games.


I am honored to have opportunities to work with the following faculty members and researchers (A-Z):

  • Joshua A. Auld, Principal Engineer, Argonne National Laboratory
  • Zhibin Chen, Assistant Professor, Engineering, NYU Shanghai
  • Xuan Sharon Di, Assistant Professor, Civil Engineering, Columbia University
  • Robert C. Hampshire, Associate Professor, Ford School of Public Policy, University of Michigan
  • Zhiyuan Huang, Assistant Professor, School of Economics and Management, Tongji University
  • Henry Lam, Associate Professor, Industrial Engineering and Operations Research, Columbia University
  • Viswanath Nagarajan, Assistant Professor, Industrial and Operations Engineering, University of Michigan
  • Huei Peng, Roger L. McCarthy Professor, Mechanical Engineering, University of Michigan
  • Romesh Saigal, Professor, Industrial and Operations Engineering, University of Michigan
  • Cong Shi, Associate Professor, Industrial and Operations Engineering, University of Michigan
  • Yafeng Yin, Professor, Civil and Environmental Engineering, University of Michigan

Operations Research for Social Good:

Technology for Social Good refers to the use of technology – broadly engineering, applied science and computing-based artifacts, algorithm and techniques – towards addressing pressing social problems.

— Ellen Zegura, Georgia Institute of Technology

As an engineer, I believe that using scientific principles to solve real-world problems is our prior mission. Some of my research are inspired by the hassles in our daily commuting, collaboration in teams, and operations of complex systems.

For example, we studied how to improve parking systems by data analytics, and how to use data to make product replenishment more efficiently.