My name is Zhanhong Cheng (程展鸿). I am a postdoctoral researcher in the Department of Civil Engineering at McGill University. My research focuses on developing data-driven and knowledge-driven solutions for intelligent, sustainable, and accessible transportation. Drawing on techniques such as machine learning, statistical modeling, optimization, and transportation network analysis, I develop applications and discover knowledge from massive multi-modal transportation data. Find more about me on CV, Google Scholar, Github, ResearchGate, or by email.
- 2023-10-27. I presented “The Regularity, Predictability, and Travel Behavior in Urban Transit Mobility” in the ITE Student Chapter at the University of Toronto. [Slides]
- 2023-09. Our paper “Probabilistic forecasting of bus travel time with a Bayesian Gaussian mixture model” was accepted by Transportation Science.
- 2023-03-14. Our paper “A large-scale empirical study on impacting factors of taxi charging station utilization” was accepted by Transportation Research Part D: Transport and Environment.
- 2023-03-04. New preprint “Traffic State Estimation with Anisotropic Gaussian Processes from Vehicle Trajectories” was available on arXiv. A small but very interesting work.
- 2022-11-09. Our paper “Real-time forecasting of metro origin-destination matrices with high-order weighted dynamic mode decomposition” was awarded the 2nd best paper award at CASPT and TransitData 2022 🏅.
- 2022-08-15. I joined as a postdoctoral researcher in Smart Transportation Lab at McGill University.
- 2022-04-25. I passed my Ph.D. oral defense.
- 2022-01-08. Paper “Real-time forecasting of metro origin-destination matrices with high-order weighted dynamic mode decomposition” accepted by Transportation Science.
- 2021-04-21. I presented the 1st edition of Zooming in on Collaborative Digital Intelligence video recording.
- 2020-12-15. I received CIRRELT Excellence Scholarship (Doctoral Rédaction).
Found more in archived news
- Cheng, Z., Trepanier, M., & Sun, L. (2022). Real-time forecasting of metro origin-destination matrices with high-order weighted dynamic mode decomposition. Transportation Science.
- Cheng, Z., Trépanier, M., & Sun, L. (2021). Incorporating travel behavior regularity into passenger flow forecasting. Transportation Research Part C: Emerging Technologies, 128, 103200.
- Wang, X., Cheng, Z., Trépanier, M., & Sun, L. (2021). Modeling bike-sharing demand using a regression model with spatially varying coefficients. Journal of Transport Geography, 93, 103059.
- Cheng, Z., Trépanier, M., & Sun, L. (2020). Probabilistic model for destination inference and travel pattern mining from smart card data. Transportation, 1-19.
- Yao, J., Cheng, Z., Dai, J., Chen, A., & An, S. (2019). Traffic assignment paradox incorporating congestion and stochastic perceived error simultaneously. Transportmetrica A: Transport Science, 15(2), 307-325.
- Yao, J., Cheng, Z., Shi, F., An, S., & Wang, J. (2018). Evaluation of exclusive bus lanes in a tri-modal road network incorporating carpooling behavior. Transport Policy, 68, 130-141.