Cheng Lyu

Cheng Lyu is a reseach associate and is working towards a PhD degree at Technical University of Munich (TUM). He obtained both his bachelor's and master's degree in Transportation Engineering from Southeast University (SEU). His research interests mainly focused on traffic prediction, shared mobility and the applications of machine learning techniques in intelligent transportation systems. He is currently working on the PANAMERA project, revolving around the development of an automotive predictive maintenance system.

Education

Nov 2021 - Present
PhD Candidate
Technical University of Munich (TUM), Munich, Germany
Sep 2018 - Jun 2021
Master of Engineering in Transportation Engineering
Southeast University, Nanjing, China
Sep 2014 - Jun 2018
Bachelor of Engineering in Transportation Engineering
Southeast University, Nanjing, China

 

Supervising

Transfer learning for transportation system resilience estimation using floating car data. (From Nov. 15, 2022. Student: Ningkang Yang)

Selected Publications

Lyu, C., Wu, X., Liu, Y., & Liu, Z. (2021). A partial-Fréchet-distance-based framework for bus route identification. IEEE Transactions on Intelligent Transportation Systems, (Early Access). https://doi.org/10.1109/TITS.2021.3069630

Lyu, C., Wu, X., Liu, Y., Liu, Z., & Yang, X. (2020). Exploring multi-scale spatial relationship between built environment and public bicycle ridership: A case study in Nanjing. Journal of Transport and Land Use, 13(1), 447–467. https://doi.org/10.5198/jtlu.2020.1568

Liu, Y., Lyu, C., Liu, Z., & Cao, J. (2021). Exploring a large-scale multi-modal transportation recommendation system. Transportation Research Part C: Emerging Technologies, 126, 103070. https://doi.org/10.1016/j.trc.2021.103070

Liu, Y., Lyu, C., Liu, X., & Liu, Z. (2020). Automatic feature engineering for bus passenger flow prediction based on modular convolutional neural network. IEEE Transactions on Intelligent Transportation Systems, 22(4), 2349–2358. https://doi.org/10.1109/TITS.2020.3004254

Liu, Y., Lyu, C., Khadka, A., Zhang, W., & Liu, Z. (2019). Spatio-temporal ensemble method for car-hailing demand prediction. IEEE Transactions on Intelligent Transportation Systems, 21(12), 5328–5333. https://doi.org/10.1109/TITS.2019.2948790