Xiaoxu Chen
Postdoc @ HEC Montréal, Canada
Ph.D. (2024) @ McGill University, Canada
M.S. (2020) @ Tongji University, China
B.S. (2017) @ Harbin Institute of Technology, China
Welcome! I am Xiaoxu Chen (陈晓旭), a 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, I worked with Prof. Lijun Sun and Prof. Martin Trépanier on statistical models with applications in transportation.
Research interests
I am interested in statistics and optimization for transportation and supply chain management. Currently, I am particularly interested in discrete choice models, spatiotemporal data modeling, and data-driven optimization under uncertainty. In the domain of transportation, I focus on probabilistic demand and travel time forecasting, statistical inference of origin-destination matrices (inverse problem), statistical modeling of passenger trip assignment in metro networks (inverse problem), and statistical modeling of driving behavior. In supply chain management, I explore problems such as statistical demand modeling and stochastic multi-echelon inventory optimization, with an emphasis on incorporating uncertainty into decision-making processes.
News
- Nov 2025: Our paper “A Bayesian Markov mesh regime-switching regression model for bus travel time forecasting” (authors: Xiaoxu Chen, Martin Trépanier, Lijun Sun) was accepted by ISTTT 2026.
- Nov 2025: Our paper “Statistical inference of boarding and alighting counts in transit systems with incomplete data” (authors: Xiaoxu Chen, Marc‑Olivier Thibault, Martin Trépanier, Lijun Sun) was accepted by Transportation Research Part C: Emerging Technologies. [Full-text]
- Jun 2025: Our paper “Bayesian inference of time-varying origin-destination matrices from boarding and alighting counts for transit services” (authors: Xiaoxu Chen, Zhanhong Cheng, Lijun Sun) was accepted by Transportation Research Part B: Methodological. [Full-text]
- Feb 2025: Our paper “Conditional forecasting of bus travel time and passenger occupancy with Bayesian Markov regime-switching vector autoregression” (authors: Xiaoxu Chen, Zhanhong Cheng, Alexandra M. Schmidt, Lijun Sun) was accepted by Transportation Research Part B: Methodological. [Full-text]
- Feb 2025: Our paper “Understanding bus delay patterns under different temporal and weather conditions: A Bayesian Gaussian mixture model” (authors: Xiaoxu Chen, Saeid Saidi, Lijun Sun) was accepted by Transportation Research Part C: Emerging Technologies. [Full-text]
- Oct 2024: I am glad to give a talk on “Bayesian inference of time-varying origin-destination matrices from boarding and alighting counts for transit services” at MIT Urban Mobility Lab. [Slides]
- Sep 2024: I am glad to give a talk on “Conditional forecasting of bus travel time and passenger occupancy with Bayesian Markov regime-switching vector autoregression” at HEC Montréal. [Slides]
Found more in archived news
Selected works
- Chen, X., Schmidt, A. M., Ma, Z., & Sun, L. (2025). Bayesian spatiotemporal modeling of passenger trip assignment in metro networks. (Under review in Annals of Applied Statistics) [Full-text]
- Chen, X., Trépanier, M., & Sun, L. (2026). A Bayesian Markov mesh regime-switching regression model for bus travel time forecasting. Transportation Research Part E: Logistics and Transportation Review, 211, 104872. [Full-text]
- Chen, X., Thibault, O., Trépanier, M., & Sun, L. (2026). Statistical inference of boarding and alighting counts in transit systems with incomplete data. Transportation Research Part C: Emerging Technologies, 183, 105484. [Full-text]
- Chen, X., Cheng, Z., & Sun, L. (2025). Bayesian inference of time-varying origin-destination matrices from boarding and alighting counts for transit services. Transportation Research Part B: Methodological, 199, 103278. [Full-text][Slides]
- Chen, X., Cheng, Z., Schmidt, A. M., & Sun, L. (2025). Conditional forecasting of bus travel time and passenger occupancy with Bayesian Markov regime-switching vector autoregression. Transportation Research Part B: Methodological, 192, 103147. [Full-text] [Slides] (Best Paper Award from TRB AED60 Statistical and Econometric Methods Committee🏅)
- Chen, X., Saidi, S., & Sun, L. (2025). Understanding bus delay patterns under different temporal and weather conditions: A Bayesian Gaussian mixture model. Transportation Research Part C: Emerging Technologies, 171, 105000. [Full-text]
- Chen, X., Cheng, Z., Jin, J. G., Trépanier, M., & Sun, L. (2023). Probabilistic forecasting of bus travel time with a Bayesian Gaussian mixture model. Transportation Science, 57(6), 1516-1535. [Full-text] [Slides]
- Chen, X., Zhang, C., Cheng, Z., Hou, Y., & Sun, L. (2023). A Bayesian Gaussian mixture model for probabilistic modeling of car-following behaviors. IEEE Transactions on Intelligent Transportation Systems, 25(6), 5880-5891. [Full-text]