Jundong Li

 

Assistant Professor
Department of Electrical and Computer Engineering
Department of Computer Science, and School of Data Science
University of Virginia

Office: E-226 Thornton Hall
Mail: 351 McCormick Road, P.O. Box 400743
Charlottesville, VA 22904-4743
Phone: 434-243-5451
Email: jundong at virginia dot edu

Biography

Jundong Li is an Assistant Professor at the University of Virginia with appointments in Department of Electrical and Computer Engineering, Department of Computer Science, and School of Data Science. Prior to joining UVA, he received his Ph.D. degree in Computer Science at Arizona State University in 2019 under the supervision of Dr. Huan Liu, M.Sc. degree in Computer Science at University of Alberta in 2014, and B.Eng. degree in Software Engineering at Zhejiang University in 2012. His research interests are generally in data mining and machine learning, with a particular focus on graph machine learning, trustworthy/safe machine learning, and more recently on large language models. He has published over 150 papers in high-impact venues (including KDD, NeurIPS, ICLR, WWW, SIGIR, WSDM, IJCAI, AAAI, SIGIR, ACL, EMNLP, CIKM, ICDM, SDM, ECML-PKDD, CSUR, TPAMI, TKDE, TKDD, TIST, etc), with over 10,000 citation count. He has won several prestigious awards, including SIGKDD Best Research Paper Award (2022), PAKDD Best Paper Award (2024), NSF CAREER Award (2022), PAKDD Early Career Research Award (2023), JP Morgan Chase Faculty Research Award (2021 & 2022), Cisco Faculty Research Award (2021), and being selected for the AAAI New Faculty Highlights roster (2021). His group's research is generously supported by NSF (CAREER, III, SaTC, SAI), DOE, Commonwealth Cyber Initiative, Jefferson Lab, JP Morgan, Cisco, and Snap.

Research Interests

  • Graph Machine Learning: Graph Neural Networks; Graph Foundation Models; Data-Efficient Learning; Fedearated Learning

  • Trustworthy Machine Learning: Causality; Fairness; Interpretation; Robustness

  • Safe Machine Learning: Anomaly/Out-of-Distribution Detection; Machine Unlearning; Attacks and Defenses

  • Large Language Models: Model Editing; Knowledge Alignment

  • AI/ML+X: Healthcare; E-commerce, Cybersecurity; Biology; Finance; Social Science; Infrastructure Systems

What's New (Archived)

  • 2024/06: Glad to receive an NSF Smart and Connected Communities (S&CC) grant " SCC-IRG Track 1: Community-Responsive Electrified and Adaptive Transit Ecosystem (CREATE): Planning, Operations, and Management".

  • 2024/06: My Ph.D. student Yushun Dong successfully defended his dissertation. He will join the Florida State University as a Tenure-track Assistant Professor from Fall 2024.

  • 2024/05: Released a comprehensive survey paper on "Safety in Graph Machine Learning: Threats and Safeguards". Please check it out!

  • 2024/05: Our paper "Interpreting Pretrained Language Models via Concept Bottlenecks" won the PAKDD 2024 Best Paper Award.

  • 2024/05: Congrautlations to Tong Zhou for winning the UVA TYDE (Thriving Youth in a Digital Environment) Undergraduate Summer Research Fellow.

  • 2024/05: Congratulations to Alexi Gladstone for winning the 2024 CS Department Louis T. R Undergraduate Research Award.

  • 2024/04: Congratulations to Zihan Chen for winning the 2024 ECE Department Ann Lee Brown Rookie of the Year Graduate Research Award.

  • 2024/03: Honored to receive the UVA Engineering Research Innovation Awards (RIA) as PI on the project of "Toward 3D Graph Foundation Models for Molecular Property Prediction".

  • 2023/11: Glad to receive a Snap gift funding on "Inductive Recommendation on Large-scale Social Networks".

  • 2023/10: Released a comprehensive survey paper on "Knowledge Editing in Large Language Model". Please check it out!

  • 2023/10: Congratulations to my Ph.D. student Song Wang for receiving the UVA Engineering School 2023-24 Endowed Graduate Fellowship.

  • 2023/08: Starting to serve as an Associate Editor for the ACM TKDD Journal.

  • 2023/08: Glad to receive a Commonwealth Cyber Initiative grant "Weakly-supervised Federated Graph Learning for Cyber-Physical Systems" as PI.

  • 2023/08: Glad to receive a DOE/Jefferson Lab grant on "Graph Learning for Efficient and Explainable Operation of Particle Accelerators" with collaborators from Jefferson Lab.

  • 2023/07: Glad to receive a 4-VA Collaborative Research Grant as Co-PI.

  • 2023/05: Honored to receive the PAKDD 2023 Early Career Research Award!

  • 2023/05: Congratulations to my Ph.D. student Jing Ma for succesfully defending her dissertation! She will join the Case Western Reserve University as a Tenure-track Assistant Professor from Fall 2023.

  • 2023/05: Congratulations to my Ph.D. student Jing Ma for receiving the CS Department John A. Stankovic Graduate Research Award.

  • 2023/04: Congratulations to my Ph.D. student Yushun Dong for receiving the ECE Department Louis T Rader Graduate Research Award (one of the only two awardees).

  • 2023/04: Congratulations to my Ph.D. student Song Wang for receiving the ECE Department Ann Lee Brown Rookie of the Year Graduate Research Award (only one awardee).