Research Interests

In the broadest sense, I do research regarding how to bridge operations research, statistics and machine learning together. I have a particular interest in studying multi-stage stochastic systems where data-driven decision making is involved, and their applications in supply chain analytics, revenue management and transportation systems. 


  • K. Ledvina, H. Qin, D. Simchi-Levi, Y. Wei. "A New Approach for Vehicle Routing with Stochastic Demand: Combining Route Assignment with Process Flexibility", Operations Research (2022). [link][SSRN]
    • Supply Chain Management SIG Meeting, MSOM Conference 2021
  • H. Qin, D. Simchi-Levi, L. Wang. "Data-Driven Approximation Schemes for Joint Pricing and Inventory Control Models", Management Science (2022). [link] [SSRN]
  • H. Qin, D. Simchi-Levi, R. Ferer, J. Mays, K. Merriam, M. Forrester, A. Hamrick. "Trading Safety Stock for Service Response Time in Inventory Positioning", Production and Operations Management (2022)[link][SSRN]. 
    • The 30th Anniversary Issue of Production and Operations Management
  • H. Qin, Z. Zhang, D. Bai. "Permutation Flowshop Group Scheduling with Position-Based Learning Effect." Computers & Industrial Engineering 92 (2016): 1-15. [link]


  • H. Hu, H. Qin, D. Simchi-Levi. "Solving Large-Scale Vehicle Routing Problems with Unsplit Demands via Limited Information", working paper. [SSRN]
  • H. Qin, D. Simchi-Levi, R. Zhu. "Provably Sample-Efficient Inventory Control", submitted. [tech report]
  • L. Chen, R. Jin, H. Qin, D. Simchi-Levi, Z. Zhang. "Distributionally Robust Omnichannel Stocking Decisions in Quick Fulfillment Systems", working paper. [SSRN]

PhD Thesis

  • H. Qin, "Stochastic Control Through a Modern Lens: Applications in Supply Chain Analytics and Logistical Systems", PhD thesis in Computational Science and Engineering, MIT, 2022. [link]
    • Winner, MIT MathWorks Prize for Outstanding CSE Doctoral Research, 2022 [link]