Zeyu Zheng

Zeyu Zheng has been a faculty member in the Department of Industrial Engineering and Operations Research at University of California Berkeley starting from 2018. He received a Ph.D. in Management Science and Engineering (2018), Ph.D. minor in Statistics (2018) and M.A. in Economics (2016) from Stanford University, and B.S. in Mathematics (2012) from Peking University. He serves as an Associate Editor for Operations Research and Probability in the Engineering and Informational Sciences. His research team works on simulation, inference, controllable generative AI models, large-scale optimization and non-stationary learning. He collaborates in addition on asset pricing and trustworthy machine learning. 

Academic background: 

• Associate Professor with tenure, UC Berkeley, 2024-

• Assistant Professor, UC Berkeley, 2018-2024

• Ph.D. in Management Science and Engineering, Ph.D. minor in Statistics, Stanford University, 2012-2018

• B.S. in Mathematics, Peking University, 2008-2012

• A Doubly Stochastic Simulator with Applications in Arrivals Modeling and Simulation (2023), Operations Research, Accepted, with Y. Zheng and T. Zhu.
• Gradient-based Simulation Optimization Algorithms via Multi-Resolution System Approximations (2023), INFORMS Journal on Computing, Published Online, with J. Xu.
• Learning to Simulate Sequentially Generated Data via Neural Networks and Wasserstein Training (2023), ACM Transactions on Modeling and Computer Simulation (TOMACS), Accepted, with T. Zhu and H. Liu. 
• Dynamic Pricing with External Information and Limited Inventory (2023), Management Science, Accepted, with X. Li.
• Immediacy Provision and Matchmaking (2023), Management Science, Volume 69(2), pp. 1245-1263, with Y. An.