Assistant Professor
Department of Information Science and Technology
George Mason University

Research Interests

  • Deep learning on graphs
  • Societal event prediction
  • Interpretable machine learning
  • Spatio-temporal data mining
  • Sparse feature learning
  • Social media mining
  • Nonconvex Optimization


  • Liang Zhao

    Dr. Liang Zhao is an assistant professor at the Department of Information Science and Technology at George Mason University. He obtained his PhD degree in 2016 from Computer Science Department at Virginia Tech in the United States. His research interests include data mining, artificial intelligence, and machine learning, with special interests in spatiotemporal and network data mining, deep learning on graphs, nonconvex optimization, and interpretable machine learning.

    He has published over 70 peer-reviewed full research papers in top-tier conferences and journals such as KDD, ICDM, TKDE, Proceedings of the IEEE, TKDD, TSAS, IJCAI, AAAI, WWW, CIKM, SIGSPATIAL, and SDM. He has been recommended for NSF Career Award in 2020. He won Best Paper Award in ICDM 2019. He has also won Jeffress Trust Award in 2019, Outstanding Doctoral Student in the Department of Computer Science at Virginia Tech in 2017, NSF CRII Award in 2018, and was ranked as one of the "top 20 Rising Star in Data Mining" by Microsoft Search in 2016. He has been helping organize several prestigious venues such as KDD 2019, ACM SIGSPATIAL 2020, SecureCom 2020, and SSTD 2017. He is co-chairing several workshops such as GeoAI 2019 co-located with SIGSPATIAL 2019 and DeepSpatial 2019 co-located with ICDM 2019.

    Highly motivated MS and PhD students who want to do research under my advisory are encouraged to contact me by my email: lzhao9@gmu.edu.



    News

    [2020-03]
    Grateful to be recommended for NSF CAREER Award.
    [2020-03]
    Survey, code, and datasets are available on the domain of "Deep Graph Generation and Transformation".
    [2020-03]
    Survey, code, and datasets are available on the domain of "Spatial and Temporal Event Prediction".
    [2020-03]
    Survey, code, and datasets are available on the domain of "Social Media Mining". 
    [2020-03]
    Survey, code, and datasets are available on the domain of "Gradient-free Optimization for Deep Neural Networks".
    [2020-02]
    One paper is accepted at TIFS.
    [2020-01]
    Students Xiaojie Guo, Yuyang Gao, and Junxiang Wang will go for research-track internship at IBM Research, Microsoft Research, and NEC Lab in Summer 2020, respectively.
    [2020-01]
    One paper is accepted at TKDE.
    [2019-12]
    One paper is accepted at AAAI 2020.
    [2019-12]
    Two papers are accepted in DATE 2020. 
    [2019-11]
    Our paper received Best Paper Award at ICDM 2019! The paper focuses on exploring an promising domain on deep graph translation. 
    [2019-09]
    One paper is accepted in ACM SIGSPATIAL 2019.
    [2019-08]
    Three papers are accepted in ICDM 2019, papers and code will be available soon.
    [2019-08]
    Two papers are accepted in CIKM 2019, papers and code will be available soon.
    [2019-08]
    The code of our KDD 2019 paper is available. Welcome to use and let us know if there is any question.
      More News...

    Awards

  • NSF CAREER Award, National Science Foundation, 2020
  • Best Paper Award, 19th IEEE International Conference on Data Mining (ICDM 2019), IEEE, 2019
  • Jeffress Trust Award, Jeffress Memorial Trust Foundation, 2018
  • NSF CRII Award, National Science Foundation, 2018
  • Outstanding Doctoral Student, Department of Computer Science, Virginia Tech, 2017
  • Top 20 Rising Stars in Data Mining, Miscrosoft Academic Search, 2016
  • First Place (Top 0.1%), China National Graduate Student Mathematics Contest in Modeling, 2010
  • First Prize (Top 5%), MITSUBISHI Automation Cup, 2009
  • Championship, Microsoft Robotics Challenge on RoboCup Wheeled Simulation, China, 2009
  • Championship, Microsoft Robotics Challenge on RoboCup Humanoid Simulation, China, 2009

  • Contact

  • Email: lzhao9@gmu.edu
  • Phone: (703)-993-5910
  • Address: Room 5343 Engineering Building, 4400 University Drive, Fairfax, VA 22030