Zhiyong Cui

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.

Research Focus

  • 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]