Cong Shi - Research

Research Interests

• Revenue Management, Supply Chain Management, Healthcare Operations, Human-Robot Interaction

• Online Learning, Offline Learning, Data-Driven Optimization, Approximation Algorithms, Online Algorithms

Under Review

• LEGO: Optimal Online Learning under Sequential Price Competition, Shukai Li, Cong Shi, Sanjay Mehrotra

• It is All About the Demand CDF: Data-Driven Periodic Review Inventory Control, Ganggang Xu, Cong Shi

• An Online Mirror Descent Learning Algorithm for Multiproduct Inventory Systems, Sichen Guo, Cong Shi, Chaolin Yang, Christos Zacharias

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

• Personalized Pricing with Invalid Instrumental Variables: Identification, Estimation, and Policy Learning, Rui Miao, Zhengling Qi, Cong Shi, Lin Lin

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

Operations Research

• Tailored Base-Surge Policies in Dual-Sourcing Inventory Systems with Demand Learning, Beryl Chen, Cong Shi, Minor Revision at Operations Research.

• Online Learning for Constrained Assortment Optimization under Markov Chain Choice Model, S. Li, Q. Luo, Z. Huang, C. Shi, Operations Research, to appear. [DOI]

• Contextual Learning with Online Convex Optimization: Theory and Application to Medical Decision-Making, E. Keyvanshokooh, M. Zhalechian, C. Shi, M. P. Van Oyen, P. Kazemian, Management Science, to appear.

  • Finalist, POMS College of Healthcare Operations Management (CHOM) Best Paper Competition, 2022.

  • Finalist, INFORMS Manufacturing & Service Operations Management (MSOM) Best Student Paper Competition, 2021.

  • Finalist, INFORMS Health Applications Society (HAS) Best Student Paper Competition, 2021.

  • Finalist, INFORMS Decision Analysis Society (DAS) Best Student Paper Competition, 2020.

  • IOE Murty Prize for Best Student Paper on Optimization, 2020.

• Online Learning for Dual Index Policies in Dual Sourcing Systems, J. Tang, B. Chen, C. Shi, Manufacturing & Service Operations Management, Vol. 26(2), 758-774, 2024. [DOI]

  • IOE Wilson Prize for Best Student Paper on Manufacturing and Service Systems, 2023.

• PASTA: Pessimistic Assortment Optimization, J. Dong, W. Mo, Z. Qi, C. Shi, E. X. Fang, V. Tarokh, International Conference on Machine Learning (ICML 2023), Honolulu, HI. [DOI]

• Online Learning and Pricing for Network Revenue Management with Reusable Resources, H. Jia, C. Shi, S. Shen, Advances in Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA. [DOI]

• Online Learning and Pricing with Reusable Resources: Linear Bandits with Sub-Exponential Rewards, H. Jia, C. Shi, S. Shen, International Conference on Machine Learning (ICML 2022), Baltimore, MD. [DOI]

• Online Learning and Pricing for Service Systems with Reusable Resources, H. Jia, C. Shi, S. Shen, Operations Research, Vol. 72(3), 1203-1241, 2024. [DOI]

• Data-Driven Hospital Admission Control: A Learning Approach, M. Zhalechian, E. Keyvanshokooh, C. Shi, M. P. Van Oyen, Operations Research, Vol. 71(6), 2111-2129, 2023. [DOI]

  • IOE Wilson Prize for Best Student Paper on Manufacturing and Service Systems, 2021.

• Network Revenue Management with Online Inverse Batch Gradient Descent Method, Y. Chen, C. Shi, Production and Operations Management, Vol. 32(7), 2123-2137, 2023. [DOI]

• Online Resource Allocation with Personalized Learning, M. Zhalechian, E. Keyvanshokooh, C. Shi, M. P. Van Oyen, Operations Research, Vol. 70(4), 2138–2161, 2022. [DOI]

• Partner with a Third-Party Delivery Service or Not? A Prediction-and-Decision Tool for Restaurants Facing Takeout Demand Surges During a Pandemic, H. Jia, S. Shen, J. Garcia, C. Shi, Service Science, Vol. 14(2), 139-155, 2022. [DOI]

• Multi-Armed Bandit with Sub-Exponential Rewards, H. Jia, C. Shi, S. Shen, Operations Research Letters, Vol. 49(5), 728-733, 2021. [DOI]

• Marrying Stochastic Gradient Descent with Bandits: Learning Algorithms for Inventory Systems with Fixed Costs, H. Yuan, Q. Luo, C. Shi, Management Science, Vol. 67(10), 6089–6115, 2021. [DOI]

  • Finalist, INFORMS Applied Probability Society (APS) Best Student Paper Competition, 2019.

  • IOE Murty Prize for Best Student Paper on Optimization, 2019.

• Nonparametric Learning Algorithms for Joint Pricing and Inventory Control with Lost-Sales and Censored Demand, B. Chen, X. Chao, C. Shi, Mathematics of Operations Research, Vol. 46(2), 405-833, 2021. [DOI]

• Online Advance Scheduling with Overtime: A Primal-Dual Approach, E. Keyvanshokooh, C. Shi, M. P. Van Oyen, Manufacturing & Service Operations Management, Vol. 23(1), 246-266, 2021. [DOI]

  • IOE Wilson Prize for Best Student Paper on Manufacturing and Service Systems, 2019.

• Optimal Learning Algorithms for Stochastic Inventory Systems with Random Capacities, W. Chen, C. Shi, I. Duenyas, Production and Operations Management, Vol. 29(7), 1624-1649, 2020. [DOI]

• Closing the Gap: A Learning Algorithm for the Lost-Sales Inventory System with Lead Times, H. Zhang, X. Chao, C. Shi, Management Science, Vol. 66(5), 1962–1980, 2020. [DOI]

• Strategic Capacity Planning Problems in Revenue Sharing Joint Ventures, R. Levi, G. Perakis, C. Shi, W. Sun, Production and Operations Management, Vol. 29(3), 664-687, 2020. [DOI]

• Joint Pricing and Inventory Management with Strategic Customers, Y. Chen, C. Shi, Operations Research, Vol. 67(6), 1610-1627, 2019. [DOI]

  • Third Place, INFORMS Junior Faculty Interest Group (JFIG) Paper Competition, 2017.

• Joint Pricing and Inventory Management with Strategic Customers, Y. Chen, C. Shi, ACM Conference on Economics and Computation (EC 2017), Cambridge, MA. [DOI]

• Process Flexibility for Multi-Period Production Systems, C. Shi, Y. Wei, Y. Zhong, Operations Research, Vol. 67(5), 1300-1320, 2019. [DOI]

• Service Level Constrained Inventory Systems, Y. Jiang, C. Shi, S. Shen, Production and Operations Management, Vol. 28(9), 2365-2389, 2019. [DOI]

• Perishable Inventory Systems: Convexity Results for Base-Stock Policies and Learning Algorithms under Censored Demand, H. Zhang, X. Chao, C. Shi, Operations Research, Vol. 66(5), 1276-1286, 2018. [DOI]

• Approximation Algorithms for Capacitated Perishable Inventory Systems with Positive Lead Times, X. Chao, X. Gong, C. Shi, C. Yang, H. Zhang, S. X. Zhou, Management Science, Vol. 64(11), 5038-5061, 2018. [DOI]

• Revenue Management of Reusable Resources with Advanced Reservations, Y. Chen, R. Levi, C. Shi, Production and Operations Management, Vol. 26(5), 836-859, 2017. [DOI]

• Production Planning Problems with Joint Service-Level Guarantee: A Computational Study, Y. Jiang, J. Xu, S. Shen, C. Shi, International Journal of Production Research, Vol. 55(1), 38-58, 2017. [DOI]

• Priority Rules for Multi-Task Due-Date Scheduling under Varying Processing Costs, Y. Xu, C. Shi, I. Duenyas, Production and Operations Management, Vol. 25(12), 2086-2102, 2016. [DOI]

• Stochastic Regret Minimization for Revenue Management Problems with Nonstationary Demands, H. Zhang, C. Shi, C. Qin, C. Hua, Naval Research Logistics, Vol. 63(6), 433-448, 2016.[DOI]

• Approximation Algorithms for Inventory Problems with Submodular or Routing Costs, V. Nagarajan, C. Shi, Mathematical Programming Series A, Vol. 160(1), 225-244, 2016. [DOI]

• A Data-Driven Approach to Manpower Planning at U.S.-Canada Border Crossings, M. Yu, Y. Ding, R. Lindsey, C. Shi, Transportation Research Part A, Vol. 91, 34-47, 2016. [DOI]

• Approximation Algorithms for Perishable Inventory Systems with Setup Costs, H. Zhang, C. Shi, X. Chao, Operations Research, Vol. 64(2), 432-440, 2016. [DOI]

• Nonparametric Data-Driven Algorithms for Multiproduct Inventory Systems with Censored Demand, C. Shi, W. Chen, I. Duenyas, Operations Research, Vol. 64(2), 362-370, 2016. [DOI]

• Approximation Algorithms for Perishable Inventory Systems, X. Chao, X. Gong, C. Shi, H. Zhang, Operations Research, Vol. 63(3), 585-601, 2015. [DOI]

• A Faster Algorithm for the Resource Allocation Problem with Convex Cost Functions, C. Shi, H. Zhang, C. Qin, Journal of Discrete Algorithms, Vol. 34, 137-146, 2015. [DOI]

• Approximation Algorithms for Capacitated Stochastic Inventory Systems with Setup Costs, C. Shi, H. Zhang, X. Chao, R. Levi, Naval Research Logistics, Vol. 61(4), 304-319, 2014. [DOI]

• Approximation Algorithms for the Stochastic Lot-Sizing Problem with Order Lead Times, R. Levi, C. Shi, Operations Research, Vol. 61(3), 593-602, 2013. [DOI]

  • First Place, INFORMS George Nicholson Student Paper Competition, 2009.

Human-Robot Interaction

• A Linear Assignment Bandit Approach to Online Multi-Human Multi-Robot Teaming, Yaohui Guo, X. Jessie Yang, Cong Shi

• Modeling Trust Propagation in Multi-Human Multi-Robot Teams, Yaohui Guo, X. Jessie Yang, Cong Shi

• Evaluating the Impact of Personalized Value Alignment in Human-Robot Interaction: Insights into Trust and Team Performance Outcomes, S. Bhat, J. B. Lyons, C. Shi, X. J. Yang

  • Accepted at International Conference on Human-Robot Interaction (HRI 2024), Boulder, CO.

• Effect of Adapting to Human Preferences on Trust in Human-Robot Teaming, S. Bhat, J. B. Lyons, C. Shi, X. J. Yang

  • Accepted at AAAI Symposium on “Agent Teaming in Mixed-Motive Situations” (2023), Arlington, VA.

• Reward Shaping for Building Trustworthy Robots in Sequential Human-Robot Interaction, Y. Guo, X. J. Yang, C. Shi

  • Accepted at International Conference on Intelligent Robots and Systems (IROS 2023), Detroit, MI.

• Enabling Team of Teams: A Trust Inference and Propagation (TIP) Model in Multi-Human Multi-Robot Teams, Y. Guo, X. J. Yang, C. Shi, Robotics: Science and Systems (RSS 2023), Daegu, South Korea. [DOI]

  • Late-Breaking Reports (LBR) at International Conference on Human-Robot Interaction (HRI 2023), Stockholm, Sweden. [DOI]

• Clustering Trust Dynamics in a Human-Robot Sequential Decision-Making Task, S. Bhat, J. B. Lyons, C. Shi, X. J. Yang, IEEE Robotics and Automation Letters, Vol. 7(4), 8815-8822, 2022. [DOI]

  • Accepted at International Conference on Intelligent Robots and Systems (IROS 2022), Kyoto, Japan.

• Reverse Psychology in Trust-Aware Human-Robot Interaction, Y. Guo, C. Shi, X. J. Yang, IEEE Robotics and Automation Letters, Vol. 6(3), 4851-4858, 2021. [DOI]

  • Accepted at International Conference on Robotics and Automation (ICRA 2021), Xi'an, China.

• Road to Micro-Celebration: The Role of Mutation Strategy of Micro-Celebrity in Digital Media, X. Chen, L. Jiang, S. Miao, C. Shi, New Media and Society, Vol. 25(12), 3455-3476, 2023. [DOI]

• Play It Safe or Leave the Comfort Zone? Optimal Content Strategies for Social Media Influencers on Streaming Video Platforms, X. Chen, L. Liang, S. Miao, C. Shi, Decision Support Systems, to appear. [DOI]

Books and Book Chapters

• The Elements of Joint Learning and Optimization in Operations Management, edited by Xi Chen, Stefanus Jasin, Cong Shi, Springer, New York, NY.

• Approximation Algorithms for Stochastic Optimization Problems in Operations Management, Encyclopedia of Operations Research and Management Science, edited by J. J. Cochran, Wiley, Hoboken, NJ.

• Approximation Algorithms for Stochastic Inventory Systems, Research Handbook on Inventory Management, edited by J.-S. Song, Edward Elgar, Cheltenham, UK.

Preprints

• Online Learning and Pricing for Network Revenue Management with Reusable Resources, Huiwen Jia, Cong Shi, Siqian Shen

• Near-Optimal Pricing Policy for Service Systems with Reusable Resources and Forward-Looking Customers, Yiwei Chen, Cong Shi

• More Bang for Your Buck: Effective KOL Marketing Campaign in Emerging Short-Video Markets, Xingyu Chen, Li Ji, Ling Jiang, Sentao Miao, Cong Shi

• Integrating Empirical Estimation and Assortment Personalization for E-Commerce: A Consider-then-Choose Model, Maggie Li, Xiang Liu, Yan Huang, Cong Shi, Cheng Hua

  • Finalist, The 2018 MSOM Data Driven Research Challenge, 2018.

External Grants

• NSF CMMI-1362619 (Co-PI), NSF CMMI-1451078 (PI), NSF CMMI-1634505 (PI).