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Hi! I am a research associate and Ph.D. candidate at the Chair of Transportation Systems Engineering at Technical University of Munich (TUM), where I have been working since November 2021.

My research focuses on machine learning for transportation systems, with emphasis on transportation demand modeling and emerging mobility solutions. I am passionate about advancing intelligent transportation systems through innovative machine learning approaches. In particular, I develop generative models and data imputation techniques to address various data challenges in modern transportation systems.

Education

2021-Now

Technical University of Munich

ThesisTackling data sparsity and data scarcity in transportation systems

Ph.D.

Munich, Germany

2025

Technical University of Denmark

Visiting

Lyngby, Denmark

2018-2021

Southeast University

ThesisData-driven framework for dynamic urban road capacity estimation

M.Eng.

Nanjing, China

2014-2018

Southeast University

ThesisSpatial analysis of bike-sharing ridership patterns and its relationship with urban built environment

B.Eng.

Nanjing, China

News

07.2025

Our work "A diffusion-based Expectation-Maximization framework for probabilistic traffic data imputation" was accepted by IEEE IOTJ 🎉!

Publications

More

2025

Lyu, C., Wu, H., Li, D., Pereira, F. C., Azevedo, C. M. A., & Antoniou, C. (2025). Improving Fidelity and Diversity of Population Synthesis via Latent Generative Flow. Under Review.

2025

Lyu, C., & Antoniou, C. (2025). A Diffusion-Based Expectation-Maximization Framework for Probabilistic Traffic Data Imputation. IEEE Internet of Things Journal, 12(20), 43227–43240.

Paper Code

2024

Lyu, C., Lu, Q. L., Wu, X., & Antoniou, C. (2024). Tucker Factorization-Based Tensor Completion for Robust Traffic Data Imputation. Transportation Research Part C: Emerging Technologies, 160, 104502.

Paper Code

2022

Lyu, C., Liu, Y., Wang, L., & Qu, X. (2022). Personalized Modeling of Travel Behaviors and Traffic Dynamics. Journal of Transportation Engineering, Part A: Systems, 148, 04022081.

Paper

2021

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, 23(7), 9275–9280.

Paper

2020

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, 447–467.

Paper

Awards

2022

NeurIPS Traffic4cast Challenge — Extended Track

City-wide traffic forecasting with partially observed traffic sensors

Second Place

2020

ACM SIGKDD — KDD Cup 2020 Reinforcement Learning Track

Dispatching and repositioning on a mobility-on-demand platform

First Place

2019

ACM SIGKDD — KDD Cup 2019 Regular Machine Learning Track

Context-aware multi-modal transportation recommendation

Second Place

2019

National College New Energy Vehicle Big Data Innovation Competition

Electric vehicles mileage prediction

First Place

2019

National College Big Data Application Competition

Multi-task weather prediction in urban areas

First Place

2019

IEEE ICME Grand Challenges on Short Video Understanding

Short video understanding and recommendation

Third Place

2021

Distinguished Master Thesis

2020

National Scholarship

2019

National Scholarship