Yingxue Zhang

Yingxue Zhang

Assistant Professor

Computer Science

Binghamton University

Email: yzhang42@binghamton.edu

Biography

Yingxue Zhang is an Assistant Professor in Computer Science Department at Binghamton University. She got her Ph.D. degree in Data Science from Worcester Polytechnic Institute in 2022. Her broad research interests include: (1) designing novel data mining, machine learning and AI techniques to solve spatial-temporal big data analytics problems related to smart cities and public safety, and (2) human behavior analysis and decision making.

Download CV.

Openings: I am looking for self-motivated PhD students to work on deep learning topics. I’m particularly interested in candidates with background in CS/AI/Data Mining/Machine Learning/Stat/Math and strong programming skills. Please send me a short email with your CV and transcript.

Interests
  • Artificial Intelligence
  • Deep Learning
  • Meta-Learning
  • Imitation Learning
  • Spatial-Temporal Data Mining
Education

  • PhD in Data Science, 2022

    Worcester Polytechnic Institute

  • MS in Financial Engineering, 2018

    Stevens Institute of Technology

  • BS in Computer Science, 2012

    Shanghai Jiao Tong University

Recent News

  • [TPC] 01/2023: PC for KDD 2023 and IJCAI 2023.
  • [Paper] 12/2022: One paper was accepted by SDM 2023!
  • [Paper] 09/2022: Two papers were accepted by ICDM 2022!
  • [Position] 08/2022: Joined the Computer Science Department at Binghamton University as an Assistant Professor!
  • [TPC] 03/2022: PC for KDD 2022

Publications

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Yingxue Zhang, Yanhua Li, Xun Zhou, Ziming Zhang, and Jun Luo (2022). STM-GAIL: Spatial-Temporal Meta-GAIL for Learning Diverse Human Driving Strategies. SIAM International Conference on Data Mining (SDM23), Minneapolis, April 27 - 39, 2023. (27.5% = 105/382 Acceptance Ratio).

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Yingxue Zhang, Yanhua Li, Xun Zhou, and Jun Luo (2022). Mest-GAN: Cross-City Urban Traffic Estimation with Meta Spatial-Temporal Generative Adversarial Networks. IEEE International Conference on Data Mining, (9.77%=85/870 Full paper acceptance ratio), Orlando, FL, Nov. 28 - Dec 1, 2022.

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Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, and Jun Luo (2022). STrans-GAN: Spatially-Transferable Generative Adversarial Networks for Urban Traffic Estimation. IEEE International Conference on Data Mining, (9.77%=85/870 Full paper acceptance ratio), Orlando, FL, Nov. 28 - Dec 1, 2022.

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Yingxue Zhang, Yanhua Li, Xun Zhou, Zhenming Liu, Jun Luo (2021). C3-GAN: Complex-Condition-Controlled Urban Traffic Estimation though Generative Adversarial Networks. In 2021 IEEE International Conference on Data Mining (ICDM 2021).

PDF Cite

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).

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Teaching

  • INFO 501 Information Systems I-Python and Data Mining
  • INFO 535 Applied Data Mining
  • INFO 536 Applied Machine Learning

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