Jingwen Tang

Hi! I am a fifth-year Ph.D. candidate at the Department of Industrial and Operations Engineering (IOE) at the University of Michigan, Ann Arbor, where I am extremely fortunate to be advised by Professor Cong Shi. My current research interests lie broadly in learning algorithms and data-driven optimization. Specific topics include sequential decision-making under uncertainty and online and offline learning algorithms, especially their applications in supply chain management and revenue management. Before joining the University of Michigan, I earned my Bachelor's degree in Industrial Engineering from Tsinghua University. I will join the Department of Management at Miami Herbert Business School, University of Miami as an Assistant Professor starting July 2024. Email: tjingwen [at] umich [dot] edu [Curriculum Vitae]

Education

• Ph.D. in Operations Research (2019 - present), University of Michigan, Ann Arbor, MI. Advisor: Professor Cong Shi.
  Joint Ph.D. in Scientific Computing (2021 - present)
  

• B.S. in Industrial Engineering (2015 - 2019), Tsinghua University, Beijing, China.

Research Interests

• Methodologies: Online Learning Algorithms, Approximation Algorithms

• Applications: Supply Chain Management, Revenue Management, Service Systems

Journal Publications

• Online Learning for Dual Index Policies in Dual Sourcing Systems, Jingwen Tang, Boxiao (Beryl) Chen, Cong Shi, Manufacturing & Service Operations Management. [DOI]

  • Winner, Richard C. Wilson Prize for Best Student Paper, 2023.

Working Papers

• Multiproduct Inventory Systems with Upgrading: Replenishment, Allocation, and Online Learning, Jingwen Tang, Izak Duenyas, Cong Shi, Nan Yang.

• Offline Feature-Based Pricing under Censored Demand: A Causal Inference Approach, Jingwen Tang, Zhengling Qi, Xingyuan (Ethan) Fang, Cong Shi.

• Remunerating Newsvendor Problem in a Two-Sided Market, Jingwen Tang, Cong Shi, Izak Duenyas.