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 over a hundred papers in top-tier conferences and journals such as KDD, ICDM, TKDE, NeurIPS, 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 2021, 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 the mentor of Computing Innovative Fellowship 2021. He is a senior member of IEEE.

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


    Excited to receive Meta Research Award with Yue Cheng from UVA!
    Two papers are accepted in NeurIPS 2022 on periodic graph generation and controllable data generation.
    Two papers are accepted in SIGSPATIAL 2022 on trajectory generation and spatial data fusion.
    Three papers are accepted in ICDM 2022 on three existing topics: spatial domain generalization, explanation supervision, and analogical reasoning.
    Welcome to attend our KDD 2022 and IJCAI 2022 tutorials on Graph Neural Networks, and visit our website for materials.
    Our GraphGT Data Repository is online, with 30+ datasets&APIs for graph generation in machine learning!
    Three papers are accepted in KDD 2022 on three exciting areas: explanation supervision, graph inverse problems, and saliency-regularized multitask learning.
    Our new book Graph Neural Network: Foundations, Frontiers, and Applications (689 pages, ISBN-10: 9811660530, Springer) is published. You can also access various resources about it in our book website.
    Our paper "Deep Graph Translation" is accepted in TNNLS.
    Our paper on Heterogeneous Graph Generation is selected as Best Paper Candidate at ICDM 2021!
    Three papers are accepted in AAAI 2022.
    Two papers are accepted in NeurIPS 2021.
    Two papers are accepted in ICDM 2021 on the topics of "heterogeneous graph generation" and "interactive learning for model interpretation".
    Our paper on neuro-inspired machine learning has been accepted by Neural Networks.
    I have been elevated to IEEE Senior Member.
    Dr. Yun Li is named a 2021 Computing Innovation Fellow by CRA and CCC with me as the mentor.
    Our EPIDE website is released: A large data repository for event prediction based on my CSUR paper.
    Our paper on disentangled representation learning won the Best Paper Award Shortlist in WWW 2021!
    Congratulations to Xiaojie Guo on her Ph.D. graduation and her new position in JD.COM as research scientist.
    I am grateful for receiving AWS Machine Learning Research Award!
    Our paper "Deep Graph Transformation for Attributed, Directed, and Signed Networks" has been accepted by Knowledge and Information Systems as Bests of ICDM!
    My work "Event Prediction in the Big Data Era: A Systematic Survey" has been accepted by ACM Computing Surveys (IF: 7.990)!
    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.
    A paper on "Property Controllable Variational Autoencoder via Invertible Mutual Dependence" has been accepted in ICLR 2021.
      Older News...


  • Meta Research Award, Meta Platforms, Inc. (formerly Facebook), 2022.
  • KAIS on "Bests of ICDM", Springer, 2022
  • Best Paper Candidate, the 21st IEEE International Conference on Data Mining (ICDM 2021), IEEE, 2021
  • 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
  • NSF Computing Innovation (CI) Fellow Mentor, 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