Zhuodong Tang (唐卓栋)
Postdoctoral Research Fellow
Stephen M. Ross School of Business, University of Michigan
Welcome! I am Zhuodong Tang, a postdoctoral research fellow at the Stephen M. Ross School of Business, University of Michigan, under the guidance of Prof. Izak Duenyas and Prof. Stefanus Jasin. I received my Ph.D. degree in 2022 from the Department of Industrial Engineering and Decision Analytics, Hong Kong University of Science and Technology, where I was fortunate to be advised by Prof. Guillermo Gallego. Before my Ph.D. journey, I received my Bachelor's degree in Automation from Zhejiang University in 2017.
I am on the 2023-2024 academic job market.
Research Interest
My research focuses on developing novel discrete choice models and solving revenue management problems such as assortment optimization and pricing under the choice model. I am also interested in data-driven operations management (OM) models that unite the predictive power of machine learning and business insights of OM models. My research collaborates with leading industrial companies, including Hewlett Packard and Sabre Airline.
Upcoming Talks
INFORMS Annual Meeting, Phoenix, Arizona, Oct. 15 - 18, 2023
Title: "On the Performance of Myopic and Revenue-Ordered Policies for a Multi-Period Assortment Optimization under an MNL Model with Popularity Bias"
Time: October 16, 12:45 PM - 2:00 PM Location: CC-North 121B
Publications
"Estimating Discrete Choice Models with Random Forests" (with Ningyuan Chen and Guillermo Gallego), INFORMS International Conference on Service Science, 2021.
Working Papers
[1] "The Threshold Utility Model with Applications to Retailing and Choice Models" (with Guillermo Gallego and Ruxian Wang), under major revision at Manufacturing & Service Operations Management.
[2] "The Use of Binary Choice Forest to Model and Estimate Discrete Choices" (with Ningyuan Chen and Guillermo Gallego), under the second round review at Operations Research.
Finalist of Best Student Paper Competition, INFORMS International Conference on Service Science, 2021
Selected for Spotlight Talk at INFORMS Revenue Management and Pricing (RMP) Section International Conference, 2021
[3] "On the Performance of Myopic and Revenue-Ordered Policies for a Multi-Period Assortment Optimization under an MNL Model with Popularity Bias" (with Stefanus Jasin and Izak Duenyas), under review at Operations Research. (Job market paper)
Presented at INFORMS MSOM Conference, 2023
[4] Pricing Multiple Products and Competition Analysis under the Threshold Utility Model (with Guillermo Gallego and Ruxian Wang), Reject & Resubmit at Manufacturing & Service Operations Management.
Presented at INFORMS Annual Meeting, 2022
[5] Product Line Design and Pricing under Mixed Basic Attraction Model (with Guillermo Gallego and Anran Li), to be soon submitted.
Presented at INFORMS Annual Meeting, 2020
Collaboration with Hewlett Packard (HP)