I am a PhD Candidate in the Smart Transportation Application and Research Lab (STAR Lab) in the Department of Civil & Environmental Engineering at the University of Washington advised by Prof. Yinhai Wang. I received my Master degree in Software Engineering from Peking University and my Bachelor degree in Software Engineering from Beihang University. I was a visiting master student in the College of Electrical Engineering and Computer Science at National Taiwan University advised by Prof. Hsin-Mu (Michael) Tsai.
- Basic and Applied Research on Machine Learning and Deep Learning
- Urban Computing & Transportation Data Science
- Spatiotemporal Data Modeling/Imputation/Prediction
- Connected Vehicles and Autonomous Driving
News Over the Past Half Year
- New! Jan. 2020. I’m honoured to win the Student Paper Award from the Transportation Statistics Interest Group of American Statistical Association (ASA). [Paper]
- New! Oct. 2019. Two first-author and two co-authored papers are accepted for presentation at TRB 2020.
- New! Oct. 2019. I win the Second Prize in the 2019 PacTrans Annual Conference best poster contest.
- New! Oct. 2019. I give a talk at INFORMS 2019 entitled: “Learning Traffic as a Graph: Graph based Neural networks for Network-scale Traffic Prediction” [link]
- New! Sept. 2019. My first-author paper “Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting” is accepted by IEEE Transaction on Intelligent Transportation Systems [arXiv][code]
- New! Sept. 2019. My first-author paper “Establishing a Multi-Source Data Integration Framework for Transportation Data Analytics” is accepted by Journal of Transportation Engineering, Part A: Systems
- New! Aug. 2019. My first-author paper “Perspectives on Stability and Mobility of Transit Passenger’s Travel Behavior through Smart Card Data” is accepted by IET Intelligent Transport Systems [doi]
- New! June 2019. Our invited review article “The Development of Smart Transportation in Urgent Need of Transportation Data Science (in Chinese)” is publised at Urban Transport of China [doi]
Selected Research on Deep Learning based Traffic Prediction and Data Imputation
Cui Z, Lin L, Pu Z, Wang Y. (2020) Graph Markov Network for Traffic Forecasting with Missing Data. Transportation Research Board 99th Annual Meeting [arXiv] (ASA TSIG Student Paper Award)
Cui, Z., Henrickson, K., Ke, R., & Wang, Y.* (2019). Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting. IEEE Transaction on Intelligent Transportation Systems [arXiv][code][data]
Cui, Z., Ke, R., & Wang, Y.* (2018). Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction. (submitted to IEEE Transaction on Intelligent Transportation Systems; under review). [arXiv][code][data]
Liang, Y., Cui, Z., Tian, Y., Chen, H., & Wang, Y.* (2018). A Deep Generative Adversarial Architecture for Network-Wide Spatial-Temporal Traffic State Estimation. Transportation Research Record. [arXiv]