Assistant Professor
Department of Computer Science
Emory 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 Computer Science at Emory University. He was an assistant professor at the Department of IST and CS 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 numerous 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 won NSF CAREER Award in 2020. He has also won Amazon Research Award in 2020 and 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 won best papers and best paper candidates in top-tier venues such as ICDM 2019 and WWW 2021. He has been organizing several prestigious venues such as KDD 2019, ACM SIGSPATIAL 2020, ICDM 2019, CIKM 2019, SecureCom 2020, and SSTD 2017. He is co-chairing workshops such as GeoAI co-located with SIGSPATIAL and DeepSpatial co-located with KDD.

    My group is constantly searching for highly-motivated students. Those who are interested are encouraged to contact me: liang.zhao_at_emory_dot_edu




    News

    [2021-08]
    Two papers are accepted in ICDM 2021 on the topics of "heterogeneous graph generation" and "interactive learning for model interpretation".
    [2021-08]
    Our paper on neuro-inspired machine learning has been accepted by Neural Networks.
    [2021-07]
    I have been elevated to IEEE Senior Member.
    [2021-06]
    Dr. Yun Li is named a 2021 Computing Innovation Fellow by CRA and CCC with me as the mentor.
    [2021-06]
    Our EPIDE website is released: A large data repository for event prediction based on my CSUR paper.
    [2021-04]
    Our paper on disentangled representation learning won the Best Paper Award Shortlist in WWW 2021!
    [2021-04]
    Congratulations to Xiaojie Guo on her Ph.D. graduation and her new position in JD.COM as research scientist.
    [2021-02]
    I am grateful for receiving AWS Machine Learning Research Award!
    [2021-02]
    Our paper "Deep Graph Transformation for Attributed, Directed, and Signed Networks" has been accepted by Knowledge and Information Systems as Bests of ICDM!
    [2021-02]
    My work "Event Prediction in the Big Data Era: A Systematic Survey" has been accepted by ACM Computing Surveys (IF: 7.990)!
    [2021-01]
    Two papers are accepted in WWW 2021: one is for temporal graph deep generative models, the other is on disentangled representation learning for COVID-19 analysis.
    [2021-01]
    A paper on "Property Controllable Variational Autoencoder via Invertible Mutual Dependence" has been accepted in ICLR 2021.
    [2020-12]
    A paper on "Deep Graph Spectral Evolution Networks for Graph Topological Evolution" has been accepted in AAAI 2021.
    [2020-12]
    A paper on "Disentangled Dynamic Graph Deep Generation" has been accepted in SDM 2021.
    [2020-08]
    [2020-08]
    Two papers on Model-parallelism Deep Learning and Heterogeneous Graph Neural Networks are accepted in ICDM 2020.
    [2020-08]
    I am grateful for receiving a research grant ($498K) from NSF on the project III: Small: Deep Generative Models for Temporal Graph Generation and Interpretation.
    [2020-07]
    [2020-07]
    [2020-07]
    I am grateful for receiving a research grant ($499K) from NSF on the project "DeepJIMU: Model-Parallelism Infrastructure for Large-scale Deep Learning by Gradient-Free Optimization"!
    [2020-07]
    I am grateful for receiving a research grant ($510K) from Knowledge Design Company on the project "Secure Model and Learning protected Hardware Design"!
    [2020-07]
    My student Qingzhe Li has passed his final defense. Congratulations, Dr. Li!
    [2020-06]
      Older News...

    Awards

  • Best Paper Award Shortlist, 30th International World Wide Web Conferences (WWW 2021), ACM, 2021
  • AWS Machine Learning Research Awards, Amazon Science, 2020
  • KAIS on "Bests of ICDM", Springer, 2020
  • 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: liang.zhao_at_emory_dot_edu
  • Phone: (703)-993-5910
  • Address: Room 5343 Engineering Building, 4400 University Drive, Fairfax, VA 22030