Preprints

• Jiang, Yiming, and He Wang. “Causal Inference under Network Interference Using a Mixture of Randomized Experiments.” ArXiv. /abs/2309.00141.
  • Finalist, 2023 Revenue Management and Pricing Section Jeff McGill Student Paper Award
• Cao, Yufeng, Anton Kleywegt, and He Wang. “Dynamic Pricing for Two-sided Marketplaces with Offer Expiration.” Under review at Management Science (major revision).

Book Chapter

• Chen, Qi, He Wang, and Zizhuo Wang. (2022). “Learning and Pricing with Inventory Constraints.” In: Xi Chen, Stefanus Jasin, Cong Shi (eds) The Elements of Joint Learning and Optimization in Operations Management. Springer Series in Supply Chain Management, vol 18. Springer, Cham.

Journal Publications

• Behrendt, Adam, Martin Savelsbergh, and He Wang. (2024). “Task assignment, pricing, and capacity planning for a hybrid fleet of centralized and decentralized couriers.” Transportation Research Part C, Vol. 160, 104553.
• Rivera Cardoso, Adrian, He Wang, and Huan Xu. (2023). “Online saddle point problem with applications to constrained online convex optimization.” Mathematics of Operations Research (accepted).
• Behrendt, Adam, Martin Savelsbergh, and He Wang. (2023). “A Prescriptive Machine Learning Method for Courier Scheduling on Crowdsourced Delivery Platforms.” Transportation Science, 57(4), 889-907. [data and code]
• Varma, Sushil Mahavir, Pornpawee Bumpensanti, Siva Theja Maguluri, and He Wang. (2023). “Dynamic pricing and matching for two-sided queues.” Operations Research, 71(1), 83-100.
  • The extended abstract appeared in ACM SIGMETRICS 2020
• Wang, Yining, and He Wang. (2022). “Constant Regret Re-solving Heuristics for Price-based Revenue Management.” Operations Research, 70(6), 3538-3557.
• Zhu, Shixiang, He Wang, and Yao Xie. (2022). “Data-Driven Optimization for Atlanta Police-Zone Design.” INFORMS Journal on Applied Analytics, 52(5), 412-432. [data and code]
  • Finalist, 2021 Daniel H. Wagner Prize (for Excellence in the Practice of Advanced Analytics and Operations Research)
  • Second place, 2019 Doing Good with Good OR Student Paper Competition (awarded to S. Zhu)
• Cao, Yufeng, Anton Kleywegt, and He Wang. (2022). “Network revenue management under a spiked multinomial logit choice model.” Operations Research, 70(4), 2237-2253. [data and code]
• Nambiar, Mila, David Simchi-Levi, and He Wang. (2021). “Dynamic inventory allocation with demand learning for seasonal goods.”  Production and Operations Management (Special Issue in Honor of Professor Hau Lee), 30(3), 750-765.
• Li, Junxuan, Alejandro Toriello, He Wang, Seth Borin, and Christina Gallarno. (2021). “Dynamic Inventory Allocation for Seasonal Merchandise at Dillard’s Inc.” INFORMS Journal on Applied Analytics, 51(4), 297-311.
• Bumpensanti, Pornpawee, and He Wang. (2020). “A re-solving heuristic with uniformly bounded loss for network revenue management.” Management Science, 66(7), 2993-3009.
  • First place, 2018 INFORMS Junior Faculty Interest Group (JFIG) Paper Competition
  • Finalist, 2018 MSOM Student Paper Competition (awarded to P. Bumpensanti)
• Nambiar, Mila, David Simchi-Levi, and He Wang. (2019). “Dynamic learning and pricing with model misspecification.” Management Science, 65(11), 4980-5000. [erratum]
  • First place, 2019 MSOM Student Paper Competition (awarded to M. Nambiar)
• Simchi-Levi, David, He Wang, and Yehua Wei. (2018). “Constraint generation for two-stage robust network flow problem.” INFORMS Journal on Optimization, 1(1), 49-70.
• Simchi-Levi, David, He Wang, and Yehua Wei. (2018). “Increasing supply chain robustness through process flexibility and inventory.” Production and Operations Management, 27(8), 1476-1491.
  • Second place, 2013 CSAMSE Best Paper Award
• Ferreira, Kris Johnson, David Simchi-Levi, and He Wang. (2018). “Online network revenue management using Thompson sampling.” Operations Research, 66(6), 1586-1602. [code download]
  • MSOM Society 2021 Operations Research Best OM Paper Award
  • Finalist, 2015 IBM Service Science Best Student Paper Award
• Cheung, Wang Chi, David Simchi-Levi, and He Wang. (2017). “Dynamic pricing and demand learning with limited price experimentation.” Operations Research, 65(6), 1722-1731.
• Wang, He, Simin Huang, Zhen Liu, and Li Zheng. (2013). “Optimal tanker chartering decisions with spot freight rate dynamics considerations.” Transportation Research Part E, 51, 109-116.

Conference Proceedings

• Zhu, Shixiang, Alexander Bukharin, Le Lu, He Wang, and Yao Xie. (2021). “Data-Driven Optimization for Police Beat Design in South Fulton, Georgia.” KDD Workshop on Data Science for Social Good.
• Varma, Sushil Mahavir, Pornpawee Bumpensanti, Siva Theja Maguluri, and He Wang. (2020). “Dynamic pricing and matching for two-sided queues.” ACM SIGMETRICS (extended abstract).
• Rivera Cardoso, Adrian, He Wang, and Huan Xu. (2019). “Large Scale Markov Decision Processes with Changing Rewards.” Advances in Neural Information Processing Systems (NeurIPS).
• Rivera Cardoso, Adrian, Jacob Abernethy, He Wang, and Huan Xu. (2019). “Competing Against Nash Equilibria in Adversarially Changing Zero-Sum Games.” International Conference on Machine Learning (ICML).

Research Grants

• National Science Foundation. “CAREER: Marketplace Design for Freight Transportation and Logistics Platforms.” Role: PI. (01/2022-12/2026)
• Georgia Tech EVPR Office (Seed Grant). “Future Cyber Manufacturing as a Service.” Role: co-PI. PI: Shreyes N. Melkote. (04/2021-03/2023)
• National Science Foundation. “Data-Driven Optimal Police Patrol Zone Districting and Staffing.” Role: PI. Co-PI: Yao Xie, George Nemhauser. (10/2020-09/2023)
• Americold. “Data-Driven Capacity Monitoring, Prediction and Planning for Hyperconnected Cold Chain Facilities.” Role: co-PI. PI: Benoit Montreuil. (01/2020-04/2021)
• Dillard’s Inc. “Dynamic Inventory Allocation in a Fashion Retail Network.” Role: PI. Co-PI: Alejandro Toriello. (08/2019-05/2020)
• Amazon Research Award. Role: PI. (05/2019-04/2020)
• SF Express. “Data-driven Design and Operation of Hyperconnected Inter-city Logistics.” Role: co-PI. PI: Benoit Montreuil, co-PIs: Alan Erera, Martin Savelsbergh, Alejandro Toriello. (08/2018-07/2021)
• Oracle. “Online Demand Learning and Prize Optimization with Endogeneity Effect.” Role: co-PI. PI: David Simchi-Levi. (05/2018-04/2019)