Scholar
Xiaoxu Chen
Google Scholar ID: PveVQZsAAAAJ
Postdoc, HEC Montréal
Citations & Impact
Citations
136
H-index
6
i10-index
4
Publications
16
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- - Paper “Bayesian inference of time-varying origin-destination matrices from boarding and alighting counts for transit services” accepted by Transportation Research Part B: Methodological
- - Paper “Conditional forecasting of bus travel time and passenger occupancy with Bayesian Markov regime-switching vector autoregression” accepted by Transportation Research Part B: Methodological
- - Paper “Understanding bus delay patterns under different temporal and weather conditions: A Bayesian Gaussian mixture model” accepted by Transportation Research Part C: Emerging Technologies
- - Gave talks at MIT Urban Mobility Lab and HEC Montréal
- - Attended TRB2025 Annual Meeting and presented work in poster session
- - Attended TRC-30 Conference and presented work in Podium session
- - Best Paper Award for “Conditional forecasting of bus travel time and passenger occupancy with Bayesian Markov regime-switching vector autoregression”
Research Experience
- - Postdoctoral Fellow in Logistics and Operations Management at HEC Montréal, working with Prof. Yossiri Adulyasak and Prof. Jean-François Cordeau on stochastic optimization in supply chain management
- - Before joining HEC Montréal, worked with Prof. Lijun Sun and Prof. Martin Trépanier on statistical models with applications in transportation
Education
- - Ph.D. (2024), Civil Engineering, McGill University, Canada, Advisors: Lijun Sun, Martin Trépanier
- - M.S. (2020), Transportation Engineering, Tongji University, China
- - B.Eng. (2017), Traffic Engineering, Harbin Institute of Technology, China
Background
- Research interests include statistics and optimization for transportation and supply chain management. Currently, particularly interested in discrete choice models, spatiotemporal data modeling, and data-driven optimization under uncertainty. In the domain of transportation, focuses on probabilistic demand and travel time forecasting, statistical inference of origin-destination matrices, statistical modeling of passenger trip assignment in metro networks, and statistical modeling of driving behavior. In supply chain management, explores problems such as statistical demand modeling and stochastic multi-echelon inventory optimization, with an emphasis on incorporating uncertainty into decision-making processes.
Co-authors