Our Faculty

headshot of Yingxue Zhang

Yingxue Zhang

Assistant Professor

School of Computing
EB N04

Background

Zhang is an assistant professor in the School of Computing at °®¶¹´«Ã½. She got her PhD in data science from Worcester Polytechnic Institute in 2022. Her broad research interests include:

  • Designing novel data mining, machine learning and AI techniques to solve spatial-temporal big data analytics problems related to smart cities and public safety
  • Human behavior analysis and decision-making

Publications

  • Yingxue Zhang, Yanhua Li, Xun Zhou, Zhenming Liu, Jun Luo (2021). C3-GAN: Complex-Condition-Controlled Urban Traffic Estimation through Generative Adversarial Networks. In 2021 IEEE International Conference on Data Mining (ICDM 2021).
  • Yingxue Zhang, Yanhua Li, Xun Zhou, Jun Luo, Zhi-Li Zhang (2021). Urban Traffic Dynamics Prediction---A Continuous Meta-Learning Approach. In ACM Transactions on Intelligent Systems and Technology (TIST).
  • Han Bao, Xun Zhou, Yiqun Xie, Yingxue Zhang, Yanhua Li (2021). COVID-GAN+: Estimating Human Mobility Responses to COVID-19 through Spatio-Temporal Generative Adversarial Networks with Enhanced Features. In ACM Transactions on Intelligent Systems and Technology (TIST).
    Yingxue Zhang, Yanhua Li, Xun Zhou, Jun Luo (2020). cST-ML: Continuous Spatial-Temporal Meta-Learning for Traffic Dynamics Prediction. In 2020 IEEE International Conference on Data Mining (ICDM).
  • Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo (2020). Off-Deployment Traffic Estimation — A Traffic Generative Adversarial Networks Approach. In IEEE Transactions on Big Data.
  • Han Bao, Xun Zhou, Yingxue Zhang, Yanhua Li, Yiqun Xie (2020). COVID-GAN: Esti-mating Human Mobility Responses to COVID-19 Pandemic through Spatio-Temporal Conditional GenerativeAdversarial Networks. In Proceedings of the 28th ACM SIGSPATIAL International Conference on Advances inGeographic Information Systems (SIGSPATIAL).
  • Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo (2020). Curb-GAN: Conditional Urban Traffic Estimation through Spatio-Temporal Generative Adversarial Networks. In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
  • Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo (2019). TrafficGAN: Off-Deployment Traffic Estimation with Traffic Generative Adversarial Networks. In 2019 IEEE International Conference on Data Mining (ICDM).

Education

  • PhD, Worcester Polytechnic Institute
  • MS, Stevens Institute of Technology
  • BS, Shanghai Jiao Tong University

Research Interests

  • Deep learning
  • Meta-learning
  • Imitation learning
  • Spatial-temporal data mining