I am Qi Luo, an Assistant Professor at Clemson University.
E-mail: qluo2 (at) clemson.edu Office: 277B Freeman
Biography
Dr. Luo is an Assistant Professor in the Department of Industrial Engineering and the School of Mathematical and Statistical Sciences (joint) at Clemson University. He is affiliated with Clemson Operations Research Institute and the Artificial Intelligence Research Institute for Science and Engineering (AIRISE).
His primary research interest is in the areas of data-driven decision-making in operations management and emerging mobility systems. His research has been recognized by prizes such as the TRB Kikuchi-Karlaftis Best Paper Award, the INFORMS APS Best Student Paper (finalist) and IEEE I-Sim Best Student Paper.
News
- DIALab (Decision Intelligence & Analytics Lab) at Clemson University is actively looking for Ph.D./M.S. students with sound backgrounds in mathematical modeling and data analytics (enroll in 2024)!
- Please read the requirements of IE graduate program
- If you are interested, please send your CV + one-page study plan.
- July 2023: Welcome Lu Liu to join our lab! He obtained a M.S. degree in Operational Research with Data Science from the University of Edinburgh.
- May 2023: Dr. Qi Luo (PI) received a research grant entitled “Early-Stage Clinical Trials with Patient Choice”(CMMI-2308750) from the National Science Foundation. This three-year research grant (co-PI: Amin Khademi) will innovate patient-centric clinical trials using information-based behavior models and expand the limits of dynamic games and market design.
- 2022-2023: rl-transport.org is released!
- A group of students helped create two functional tools for disseminating the recent development of data-driven and reinforcement learning methods in transportation research.
- A search engine for clustered research topics and their trends over time.
- An open textbook for RL in transportation research.
- August 2022: Welcome Yan Wu to join our lab! She is co-advised by Dr. Yuyuan (Lance) Ouyang from SMSS. She obtained a M.S. degree from OR in SMSS at Clemson University.
- April 2022: Dr. Luo (co-PI) was awarded a NSF grant titled “Adapting to the Future of Robotic Surgery: Understanding Training and Design Environments for Human-Robot Teams“.
- January 2022: Dr. Luo (co-PI) was awarded a SAGES Robotics grant titled “Enter Personalized Robotic Surgery Training to Optimize Learning Outcomes“.
- August 2021: Welcome Hanwen Liu to join our lab! He graduated with a M.S. from the University of Florida.
- January 2021: Dr. Luo and his collaborators won the 2021 Kikuchi-Karlaftis Best Paper Award from the TRB Artificial Intelligence and Advanced Computing Applications (AIACA) committee for their work ‘Optimizing matching time intervals for ride-hailing services using reinforcement learning.‘
- FY 2020-2021:
- Dr. Luo is in the organizing committee for the 2021 International Symposium on Transportation Data and Modeling (ISTDM) on June 21–23, 2021 in Ann Arbor, Michigan.
- Dr. Luo 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. (archived link)
- How to mitigate the risk of taking public transit and distribute vaccines during the outbreak of pandemic? We are working with researchers from Weill Cornell Medicine, Vanderbilt University, and Rutgers University on modeling the best practice in addressing this timely issue.
- FY 2019-2020:
- 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.
DIALab (Decision Intelligence & Analytics Lab) at Clemson University focuses on exploring the mathematical foundations (optimization, statistics, and learning models) that comprise prescriptive analytics.
Our ongoing projects include creating equal access to emerging mobility systems, personalizing healthcare services, and improving digital supply chains.
Current DIALab Members:
Ph.D. student in Industrial Engineering
M.S. University of Florida
B.A. Shandong University
Research projects:
Sequential decision-making in evacuations and healthcare systems.
Email: hanwen@clemson.edu
Ph.D. student in Industrial Engineering
M.S. Clemson University
B.S. China Agricultural University
Research projects:
Reinforcement learning and transportation (co-advised with Yuyuan ‘Lance’ Ouyang in SMSS)
Email: yw8@clemson.edu
Ph.D. student in Industrial Engineering
M.S. University of Edinburgh M.S.E. University of Science and Technology of China
Research projects:
Smart mobility and machine learning.
Email: lliu6@clemson.edu
Undergrad student in Industrial Engineering
Email: dlor@clemson.edu
Undergrad student in Computer Science
Email: janett@clemson.edu
Former Lab Members:
| Name | Degree/Role | Year | First Placement |
|---|---|---|---|
| Shidi Deng | M.S. (Université Clermont Auvergne) | 2022 | Technical University of Munich School of Management |
| Richard Bozard | B.E. (Clemson University) | 2022 | |
| Ben Wang | Ph.D. (University of Michigan), visiting scholar | 2022 | Tesla |
| Sanjana Narayana | M.S. (Clemson University) | 2021 | Western Digital |
| Akshay Ashwin Shah | M.S. (Clemson University) | 2021 | Gestamp Auto |
Research & Publication
Emerging Mobility Market
Reinvent passenger and goods transportation in the digital age
Refereed Articles Published
- Luo, Qi, Viswanath Nagarajan, Alexander Sundt, Yafeng Yin, John Vincent, and Mehrdad Shahabi. “Efficient Algorithms for Stochastic Ride-Pooling Assignment with Mixed Fleets.” Transportation Science (2023).
- Sun, Ruixiao, Qi Luo, and Yuche Chen. “Online transportation network cyber-attack detection based on stationary sensor data.” Transportation Research Part C: Emerging Technologies 149 (2023): 104058.
- Dong, Tingting, Xiaotong Sun, Qi Luo, Jian Wang, and Yafeng Yin. “The Dual Effects of Team Contest Design on On-Demand Service Work Schedules.” Service Science (2023).
- Dong, Tingting, Zhengtian Xu, Qi Luo, Yafeng Yin, Jian Wang, and Jieping Ye. “Optimal contract design for ride-sourcing services under dual sourcing.” Transportation Research Part B: Methodological 146 (2021): 289-313.
- 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 (2021) 295.2 (2021): 427-442.
- 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.
- Luo, Qi, Shukai Li, and Robert Hampshire. “Optimal Design of Intermodal Mobility Networks under Uncertainty: Connecting Micromobility with Mobility-on-Demand Transit.” EURO Journal on Transportation and Logistics (2021): 100045.
Refereed Conference Proceedings
- Luo, Qi, Samitha Samaranayake, and Siddhartha Banerjee. “Multimodal Mobility Systems: Joint Optimization of Transit Network Design and Pricing.” Proceedings of the 12th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS). 2021.
- 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.
Submitted/Working Papers:
- Qin, Guoyang, Shidi Deng, Qi Luo, and Jian Sun. “Privacy-Preserving Traffic Assignment for Multimodal Transportation Systems“
- Liu, Yang, Qi Luo, Raga Gopalakrishnan, and Samitha Samaranayake. “A Framework for the Joint Optimization of Assignment and Pricing in Mobility-on-Demand Systems with Shared Rides.” arXiv preprint arXiv:2112.14297 (2021).
- Banerjee, Siddhartha, Chamsi Hssaine, Qi Luo, and Samitha Samaranayake. “Plan Your System and Price for Free: Fast Algorithms for Multimodal Transit Operations.” Available at SSRN (2021).
- Sundt, Alexander, Qi Luo, John Vincent, Mehrdad Shahabi, and Yafeng Yin. “Heuristics for Customer-focused Ride-pooling Assignment.”
Reinforcement Learning
Explore and exploit when interacting with the environment
Refereed Articles Published
- Yuan, Hao, Qi Luo, and Cong Shi. “Marrying Stochastic Gradient Descent with Bandits: Learning Algorithms for Inventory Systems with Fixed Costs.” Management Science (2021) doi.org/10.1287/mnsc.2020.3799.
- INFORMS APS 2019 Student paper competition, finalist.
- IOE at U-Mich Murty Prize 2019 for best paper on optimization.
- Qin, Guoyang, Qi Luo, Yafeng Yin, Jian Sun, and Jieping Ye. “Optimizing matching time intervals for ride-hailing services using reinforcement learning.” Transportation Research Part C: Emerging Technologies 129 (2021): 103239.
- TRB 2021 Kikuchi-Karlaftis Best Paper Award.
Submitted/Working Papers:
- Li, Shukai, Qi Luo, Zhiyuan Huang, and Cong Shi. “Online Learning for Constrained Assortment Optimization under Markov Chain Choice Model”.
Workshops and Invited Presentations:
- Qin, Guoyang, Qi Luo, Yafeng Yin, Jian Sun, and Jieping Ye. “Optimal Matching Time Interval Policy for Ride-hailing Services using Reinforcement Learning.” 100th Annual Meeting Transportation Research Board, Washington 2021.
- Yuan, Hao, Qi Luo, and Robert Hampshire. “Data-Driven Modeling of Ride-Hailing Trajectories.” Workshop in ACM SIGIR conference, Ann Arbor 2018.
Human-Engaged Models for Healthcare and Public Policy
Human-centric models can make a difference in social good
Referred Article Published
- Luo, Qi, Yunlei Yin, Pengyu Chen, Zhenfei Zhan, and Romesh Saigal. “Dynamic subsidies for synergistic development of charging infrastructure and electric vehicle adoption.” Transport Policy 129 (2022): 117-136.
- Luo, Qi, Marissa Gee, Daniel Work, Benedetto Piccoli, and Samitha Samaranayakee. “Managing public transit during a pandemic: the trade-off between safety and mobility” Transportation Research Part C: Emerging Technologies (2022).
- Luo, Qi, Ryan Weightman, Sean T. McQuade, Mateo Díaz, Emmanuel Trélat, William Barbour, Dan Work, Samitha Samaranayake, and Benedetto Piccoli. “Optimization of vaccination for COVID-19 in the midst of a pandemic.” Networks and Heterogeneous Media 17, no. 3 (2022): 443.
- Luo, Qi, and Romesh Saigal. “Multiagent Incentive Contracts: Existence, Uniqueness and Implementation.” Mathematics 2021, 9, 19.
Refereed Conference Proceedings
- 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.
- Luo, Qi, Marissa Gee, Daniel Work, Benedetto Piccoli, and Samitha Samaranayakee. “Managing Public Transit in the Prevalence of Pandemic and Reopening the Economy.” 100th Annual Meeting Transportation Research Board, Washington 2021.
- Yu, Fangzhou, Qi Luo, Tayo Fabusuyi, and Robert Hampshire. “A Heuristic for Learn-and-Optimize New Mobility Services with Equity and Efficiency Metrics.” 99th Annual Meeting Transportation Research Board, Washington 2020.
Submitted/Working Papers:
- 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.
Reinforcement Learning in Transportation Research
Here are useful references for researchers who are interested in using RL for transportation research (some are recommended by my students).
- Open-source platform from our lab: rl-transport.org includes open textbook for RL in transportation research.
- My graduate course IE 8490: Markov Decision Processes and Reinforcement Learning:
- Syllabus (2022, 2023)
- Problem formulation (stochastic shortest path, inventory control)
- Finite-horizon MDP
- Infinite-horizon MDP
- Temporal difference learning and Q-learning
- Stochastic gradient descent
- Multi-armed bandit
- Deep-RL and Policy Gradient
- Multi-agent RL
- Target audience: graduate students in IE, EE, CEE, CS, and applied mathematics.
- Lecture notes
I am not the author of the following sites but disseminate to anyone interested in this field:
- Optimization (especially continuous and nonlinear optimization) is the foundation of RL:
- Wiki for Optimization: Cornell University Computational Optimization Open TextbookDynamic Programming and Optimization in Game Theory
- Optimization for Machine Learning and Data Analytics
- RL is a burgeoning field:
- ML/RL Notes and Database: Super Machine Learning Revision Notes
- Data plays a significant role in RL-powered algorithms
- Gym for testing RL algorithms
- Simons Institute public lectures
- Workshop and tutorials:
- I was an organizer of Emerging Mobility Workshops/Centers/Database:EM4S Workshop (2021)
- INFORMS TSL Webinars
- Research communities and professional organizations:
- Shared-Use Mobility Center (SUMC)
- Automated vehicle research at Clemson: DeepOrange and DOT C2M2 Center
Teaching
- Markov Decision Processes and Reinforcement Learning (IE 8490, Clemson University), Spring, 2022.
- Deterministic Operations Research (IE 3800, Clemson University), Spring/Fall, 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.
Services
Journal Editorial Services (reviewer)
| Nature: Scientific Reports | 2023 – current |
| Transportation Science | 2022 – current |
| Management Science | 2021 – current |
| IISE Transactions | 2022 – current |
| European Journal of Operational Research | 2020 – current |
| Transportation Research Part B: Methodological | 2021 – current |
| Transportation Research Part C: Emerging Technologies | 2017 – current |
| Transportation Research Part E: Logistics and Transportation Review | 2018 – current |
| Transportation Research Interdisciplinary Perspectives | 2022 – current |
| Networks and Spatial Economics | 2022 – current |
| IEEE Transactions on Intelligent Transportation Systems | 2018 – current |
| Service Science | 2020 – current |
| Production and Operations Management | 2020 – current |
| Transport Policy | 2022 – current |
| ASME Journal of Manufacturing Science and Engineering | 2022 – current |
| Omega | 2021 – current |
| EURO Journal on Transportation and Logistics | 2020 – current |
| Networks | 2021 – current |
| Transportation Research Record | 2020 – current |
| Journal of Systems Science and Complexity | 2017 |
Conference Session Chair and Editorial Services
| ISTDM 2021 | Organizing committee member, International Symposium on Transportation Data and Modeling | ||
| EM4S | Organizing committee member, Emerging Mobility Systems and Services Seminar | ||
| ISTTT | Reviewer, International Symposium on Transportation and Traffic Theory | ||
| IEEE | Reviewer, Conference on Decision and Control (CDC) | ||
| IEEE | Reviewer, International Conference on Intelligent Transportation Systems (ITSC) | ||
| INFORMS | Session chair, INFORMS Annual Meeting | ||
| TRB | Transportation Research Board Annual Meeting |
Broader Impacts & Diversity
Contact
qluo2 (at) Clemson.edu
Qi Luo 罗琪
Office
277 B Freeman Hall
Department of Industrial Engineering
Clemson, SC 29634
Tel/Fax
(864) 656-5649
Qi Luo 