Qi Luo

Dr. Qi Luo is a graduate of Xi’an Jiaotong University and received a Ph.D. in Operations Research and Scientific Computing from the University of Michigan. He has worked in Argonne National Laboratory operated by the University of Chicago. Qi is currently a Postdoctoral Research Associate at Cornell University.

Qi’s primary research interest are in the areas of data-driven decision-making in operations management, mobility service systems, and gamification. His research has been recognized by prizes such as the INFORMS APS Best Student Paper (finalist) and I-Sim Best Student Paper.

• DIALab is actively looking for Ph.D. students with sound backgrounds in mathematical modeling and data analytics (Enroll in 2020).
• Qi is in an organizing committee for Emerging Mobility Systems and Services Seminar Series, a prestigious research seminar for advanced transportation studies. This weekly seminar is free to register.
• How to mitigate the risk of taking public transit during the outbreak of pandemic? We are working with researchers from Vanderbilt University and Rutgers University on modeling the best practice in addressing this timely issue.
• Joint work with Prof. Zhibin Chen (NYU Shanghai), Prof. Yafeng Yin (CEE U-M), and Prof. Romesh Saigal is reported on U-M Engineering Research News in 2020.
• Joint work with Zhiyuan Huang and Prof. Henry Lam titled “Dynamic Congestion Pricing for Ridesourcing Traffic: A Simulation-Based Approach.” won the Winter Simulation Conference I-Sim Ph.D. Colloquium Best Student Paper Award in 2019.
• Hao Yuan’s work co-authored with Qi Luo and Prof. Cong Shi titled “Marrying Stochastic Gradient Descent with Bandits: Learning Algorithms for Inventory Systems with Fixed Costs.” won the 2019 Applied Probability Society Best Student Paper competition, finalist.
• Joint work with Xuechun Dou, Prof. Sharon Di (Columbia University), and Prof. Robert C. Hampshire on connecting bikesharing and ride-hailing was reported in Ford School’s News.

• Luo, Qi, Romesh Saigal, Zhibin Chen, and Yafeng Yin, “Accelerating the Adoption of Automated Vehicles by Subsidies: A Dynamic Games Approach. ” Transportation Research Part B: Methodological, 129:226-243, 2019.
• Li, Shukai, Qi Luo, and Robert Hampshire. “Optimizing Large On-demand Transportation Systems through Stochastic Conic Programming.” European Journal of Operational Research, forthcoming.
• Luo, Qi, Xuechun Dou, Xuan Di, and Robert Hampshire. “Multimodal Connections between Micro-Mobility and Micro-transit: Conceptual Foundations and Empirical Evidence.” IEEE Intelligent Transportation Systems Magazine, forthcoming.

• Dong, Tingting, Zhengtian Xu, Qi Luo, Yafeng Yin, Jian Wang, and Jieping Ye, “Optimal Contract Design for Ride-sourcing Services under Dual Sourcing.” Revision, Transportation Research Part B: Methodological.

• Luo, Qi, Xuechun Dou, Xuan Di, and Robert Cornelius Hampshire. ”Multimodal Connections between Dockless Bike-sharing and Ride-Hailing: An Empirical Study in New York City.” In 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 2256-2261. IEEE, 2018.
• Luo, Qi, Romesh Saigal, Robert Hampshire, and Xinyi Wu. ”A Statistical Method for Parking Spaces Occupancy Detection via Automotive Radars.” In 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), pp. 1-5. IEEE, 2017.
• Wu, Xinyi, Kartik Balkumar, Qi Luo, Robert Hampshire, and Romesh Saigal. “An Evaluation of Information Sharing Parking Guidance Policies Using a Bayesian Approach.” TransportationResearch Board Annual Meeting, Washington DC 2016.

• Sundt, Alexander, Qi Luo, John Vincent, Mehrdad Shahabi, and Yafeng Yin. “Heuristics for Customer-focused Ride-pooling Assignment.” Submitted.
• Luo, Qi, Shukai Li, and Robert Hampshire. “Design of a Hub-and-Spoke Multimodal Network for the On-Demand Mobility Ecosystem: Connecting Ride-Hailing and Micro-Mobility.” Submitted.

• Yuan, Hao, Qi Luo, and Cong Shi. “Marrying Stochastic Gradient Descent with Bandits: Learning Algorithms for Inventory Systems with Fixed Costs.” forthcoming, Management Science.
  • APS 2019 Student paper competition, finalist.
  • Murty Prize 2019 for best paper on optimization.

• Qin, Guoyang, Qi Luo, Yafeng Yin, Jian Sun, and Jieping Ye. “Optimal Matching Time Interval Policy for Ride-hailing Services using Reinforcement Learning.” Submitted.

• Yuan, Hao, Qi Luo, and Robert Hampshire. “Data-Driven Modeling of Ride-Hailing Trajectories.”  Workshop in ACM SIGIR conference, Ann Arbor 2018.

• Luo, Qi, Zhiyuan Huang, and Henry Lam. “Dynamic Congestion Pricing for Ridesourcing Traffic: A Simulation-Based Approach.” Winter Simulation Conference 2019 Proceedings.
  • Winter Simulation Conference 2019 I-Sim Ph.D. Colloquium Best Student Paper Award, winner
• Yu, Fangzhou, Qi Luo, Tayo Fabusuyi, and Robert Hampshire. “A Heuristic for Learn-and-Optimize New Mobility Services with Equity and Efficiency Metrics.” 98th Annual Meeting Transportation Research Board, Washington 2020.

• Luo, Qi, Marissa Gee, Daniel Work, Benedetto Piccoli, and Samitha Samaranayakee. “Managing Public Transit in the Prevalence of Pandemic and Reopening the Economy.” Submitted
• Hampshire, Robert C., Carol Flannagan, H.V. Jagadish, Tayo Fabusuyi, Andong Chen, Eric Hanss, Oliver He, Kathleen D. Klinich, Qi Luo, Aditi Misra, and Matthew P. Reed. “A Public Health Informed Approach to Transportation Equity.” Submitted.
• Yunlei Yin, Qi Luo, Zhenfei Zhan, and Romesh Saigal,
  “Dynamic Subsidies for a Synergy between Charging Infrastructure Development and Electric Vehicle Adoption.” Submitted.
• Luo, Qi, and Romesh Saigal. “Multiagent Incentive Contracts: Existence, Uniqueness and Implementation.” Submitted.

• Deterministic Operations Research (IE 3800, Clemson University), Spring, 2021.
• Introduction to Optimization Methods (IOE 310, University of Michigan), Instructor of Record
  • Industrial and Operations Engineering, University of Michigan. Winter, 2018. 
• Transportation Network Modeling (CEE 559, University of Michigan), Guest Lecturer
  • Civil and Environmental Engineering, University of Michigan. Winter, 2019.