Associate Professor
Department of Computer Science
Emory University

Research Interests

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

  • Liang Zhao

    Dr. Liang Zhao is an associate 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 Ph.D. degree as an Outstanding Doctoral Student in the Department of Computer Science at Virginia Tech in 2017. 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 Cisco Faculty Research Award in 2023, Meta Research Award in 2022, Amazon Research Award in 2020, and Jeffress Trust Award in 2019, , and was ranked as one of the "Top 20 Rising Star in Data Mining" by Microsoft Search in 2016. He has won best paper award in ICDM 2022, best poster runner-up in ACM SIGSPATIAL 2022, Best Paper Award Shortlist in WWW 2021, Best Paper Candidate in ACM SIGSPATIAL 2022, Best Paper Award in ICDM 2019, and best paper candidate in ICDM 2021. He is recognized as "Computing Innovative Fellow Mentor" in 2021 by Computing Research Association. 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.

    Selected Recent Topics

    Visual Explanation-guided Learning: Evaluating and Correcting the Reasoning of AI models.
  • Datasets for Benchmarking XAI on Images: [Website]
  • Datasets for Benchmarking XAI on Graphs: [ChemRxiv]
  • Explanation Supervision on Images: [KDD 2022][CSCW 2022][ICCV 2023][KDD 2023]
  • Explanation Supervision on Graphs: [ICDM 2021]
  • Systematic Review: [CSUR]
  • Structure-guided Representation Learning: Disentangling Latent Features by Their Structural Semantics.
  • General Graphs: [KDD 2020]
  • Spatial Graphs: [KDD 2022][NeurIPS 2021]
  • Dynamic Graphs: [SDM 2021][WWW 2021]
  • Periodic Graphs: [NeurIPS 2022]
  • Spatiotemporal Graphs: [PKDD 2022][AAAI 2022]
  • Trajectories: [SIGSPATIAL 2022, Best Paper Candidate]
  • Controllable Data Generation: Generate New Data with Desired Properties' Values
  • Independent Properties: [ICLR 2021]
  • Correlated Properties: [NeurIPS 2022]
  • Datasets for Benchmarking Data Generation: [Website][NeurIPS 2021][TPAMI][Survey Paper 2]
  • Graph Neural Networks for Data Mining: Reframing Classic Data Mining with Gradient Descent.
  • Graph Outlier Detection [ICDM 2022, Best Paper Award]
  • Clustering: [Preprint]
  • Influence Maximization: [ICML 2023]
  • Source Localization: [KDD 2022][WWW 2022]
  • Large Language Models for Graph Mining: Transformation Between Structures and Semantics
  • Link prediction: [NeurIPS GLFrontiers 2023]
  • Trajectory mining: [preprint]
  • Survey on Domain Specialization: [preprint]

  • Awards

  • Oracle for Research Grant Award, Oracle Corporation, 2023.
  • Cisco Faculty Research Award, Cisco System Inc., 2023.
  • Middle-Career Award, IEEE Computer Society on Smart Computing, 2023
  • Best Paper Award, 22nd International Conference on Data Mining (ICDM 2022), IEEE, 2022
  • Best Poster Runner-Up Award, ACM SIGSPATIAL 2022.
  • Meta Research Award, Meta Platforms, Inc. (formerly Facebook), 2022.
  • Best Paper Candidate, ACM SIGSPATIAL 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 Fellow Mentor, Computing Research Association, 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, Microsoft Academic Search, 2016
  • First Place (1 out of 1995), 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