Huiwen Jia

Huiwen Jia is an assistant professor in the Department of Industrial Engineering and Operations Research at the University of California, Berkeley. She received her Ph.D. from the Department of Industrial and Operations Engineering at the University of Michigan, Ann Arbor, and her B.S. in Industrial Engineering from Tsinghua University. Before joining Berkeley IEOR, she was an Applied Scientist at Amazon working on two-sided online marketplace design.

Her research focuses on stochastic and robust optimization, machine learning, and online learning algorithms with applications in transportation and revenue management. She also has a particular interest in sustainable service system design.

Research Areas:

• Stochastic and Robust Optimization
• Machine Learning and Online Learning
• Transportation and Logistics
• Revenue Management

1. Online Learning and Pricing for Service Systems with Reusable Resources. Huiwen Jia, Cong Shi, and Siqian Shen. Operations Research, 2024.
2. A Shared Mobility Based Framework for Evacuation Planning and Operations Under Demand Uncertainty. Kati Moug, Huiwen Jia, and Siqian Shen. IISE Transactions, 2023.
3. Online Learning and Pricing for Network Revenue Management with Reusable Resources. Huiwen Jia, Cong Shi, and Siqian Shen. NeurIPS, 2022.
4. Online Learning and Pricing with Reusable Resources: Linear Bandit with Sub-exponential Rewards. Huiwen Jia, Cong Shi, and Siqian Shen. ICML, 2022.
5. Benders Cut Classification via Support Vector Machines for Two-stage Stochastic Integer Program. Huiwen Jia and Siqian Shen. INFORMS Journal on Optimization, 2021.
6. Scenario Grouping and Decomposition Algorithms for Chance-constrained Programs. Yan Deng, Huiwen Jia, Shabbir Ahmed, Jon Lee, and Siqian Shen. INFORMS Journal on Computing, 2020.