孙笠 Li Sun

孙笠 Li Sun

Associate Professor

About Me

I am currently an Associate Professor at North China Electric Power University (NCEPU), Beijing. I received the Ph.D. in Computer Science from Beijing University of Posts and Telecommunications in 2021, supervised by Prof. Sen Su. From September 2019 to August 2020, I was a visiting scholar at University of Illinois at Chicago, USA, advised by Prof. Philip. S. Yu (ACM/IEEE Fellow).

I am a machine learning and data mining researcher, with special attentions to Riemannian machine learning, Graphs and Cyber-security. I am granted the Young Elite Scientists Sponsorship of Beijing (2024), and I am a recipient of CIKM22 Best Paper Candidate. I have published over 30 refereed top conference/journal papers, including ICML, AAAI, IJCAI, WWW, SIGIR, ICDM, CIKM, IEEE TKDE, ACM TWEB, ACM TIST, etc. I have been routinely invited to serve as PC member in NeurIPS, AAAI, IJCAI, SIGKDD, WWW, WSDM, CIKM, etc., Publicity Chair in IEEE DSS’24 and IEEE SocialCom’23, and Guest Editor in Springer JMLC (Lead Editor) and Electronics.

News

  • [05/2024] One ICML paper is selected as Oral paper.
  • [05/2024] Be invited to serve as PC in NeurIPS 2024.
  • [05/2024] Be invited to give a talk in AMSS, Chinese Academy of Science.
  • [03/2024] Be invited to serve as Publicity Chair in IEEE DSS’24.
  • [01/2024] Be invited to serve as PC in SIGKDD 2024.
  • [01/2024] I am granted the Young Elite Scientists Sponsorship of Beijing.
  • [10/2022] One paper is selected as CIKM22 Best Paper Candidate.
  • [01/2022] One paper is selected as Top 10 Most Influential CIKM Papers at CIKM20.

Selected Publications

  1. Li Sun, Zhenhao Huang, et. al. LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering, ICML 2024, Oral, Top 1.5% (CCF-A).
  2. Li Sun, Jingbin Hu, et. al. RicciNet: Deep Clustering via A Riemannian Generative Model, ACM TheWebConf 2024 (WWW), pp. 4071-4802. (CCF-A)
  3. Li Sun, Zhenhao Huang, et. al. Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning, AAAI 2024, Oral, pp. 9044-9052. (CCF-A)
  4. Li Sun, Jingbin Hu, et. al. R-ODE: Ricci Curvature Tells When You Will Be Informed. SIGIR 2024. (CCF-A)
  5. Li Sun, Feiyang Wang, et. al. Congregate: Contrastive Graph Clustering in Curvature Spaces, IJCAI 2023. Acceptance Rate: 15%, Oral, pp. 7590-7607. (CCF-A)
  6. Li Sun, Zhongbao Zhang, et. al. Aligning Dynamic Social Networks: An Optimization over Dynamic Graph Autoencoder, IEEE TKDE, 2023, 35(6): 5597-5611. (CCF-A)
  7. Li Sun, Junda Ye, et. al. Self-supervised Continual Graph Learning in Adaptive Riemannian Spaces, AAAI 2023, pp. 4633-4642. (CCF-A)
  8. Li Sun, Junda Ye, et. al. A Self-supervised Riemannian GNN with Time Varying Curvature for Temporal Graph Learning, CIKM 2022, Best Paper Winners (6/283), Oral, pp. 1827-1836. (CCF-B, Best Paper Candidate)
  9. Li Sun, Zhongbao Zhang, et. al. A Self-supervised Mixed-curvature Graph Neural Network, AAAI 2022, pp. 4146-4155. Acceptance Rate: 15%, Oral. (CCF-A)
  10. Li Sun, Zhongbao Zhang, et. al. Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs, AAAI 2021, pp. 4375-4383. Oral. (CCF-A)
  11. Dou, Y., Liu, Z., Sun, L., et. al. Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters. CIKM20. (Top 10 Influential Papers at CIKM20)