Pan Li
Official Job Title
Assistant Professor
Email Address
Office Building
Office Room Number
Technical Interest Group(s)

Pan Li joined Georgia Tech in 2023 Spring. Before that, Pan Li worked at the Purdue Computer Science Department as an assistant professor from the 2020 fall to the 2023 Spring.  Before joining Purdue, Pan worked as a postdoc at Stanford Computer Science Department from 2019 to 2020.  Pan did his Ph.D. in Electrical and Computer Engineering at the University of Illinois Urbana-Champaign. Pan Li has got the NSF CAREER award, the Best Paper award from the Learning on Graph Conference, Sony Faculty Innovation Award, JPMorgan Faculty Award.

  • Develop and analyze more expressive, generalizable, robust machine learning algorithms with graph and geometric data, using e.g., Graph neural networks, geometric deep learning, and equivariant models.  
  • Build scalable analysis and learning tools for large-scale graph data, such as graph and hypergraph clustering algorithms, and large-scale graph machine learning.    
  • Artificial Intelligence for Science: Interpretable and trustworthy graph machine learning for physics.
Distinctions & Awards
  • NSF Career Award 2023
  • The Best Paper Award of Learning on Graph Conference, 2022
  • Sony Faculty Innovation award, 2021
  • JP Morgan Faculty award, 2021
  • ECE Distinguished Research Fellowship at UIUC 2018

Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li, "Equivariant Hypergraph Diffusion Neural Operators," ICLR 2023    

Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li, "Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective", NeurIPS 2022     

Haoyu Wang, Nan Wu, Hang Yang, Cong Hao, Pan Li, "Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation," NeurIPS 2022

Yuhong Luo, Pan Li, ``Neighborhood-aware Scalable Temporal Network Representation Learning,'' LoG, 2022 (best paper award).

Haoteng Yin, Muhan Zhang, Yanbang Wang, Jianguo Wang, Pan Li, ``Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning,'' VLDB, 2022.

Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li, ``Equivariant and Stable Positional Encoding for More Powerful Graph Neural Network,'' ICLR, 2022.

Siqi Miao,  Miaoyuan Liu, Pan Li, "Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism," ICML 2022

Yanbang Wang, Yen-Yu Chang, Yunyu Liu, Jure Leskovec, Pan Li, ``Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks,'' ICLR, 2021.

Pan Li, Yanbang Wang, Hongwei Wang, Jure Leskovec, ``Distance Encoding -- Design More Powerful Neural Networks for Graph Representation Learning,'' NeurIPS 2020.

Tailin Wu*, Hongyu Ren*, Pan Li, Jure Leskovec, ``Graph Information Bottleneck,'' NeurIPS 2020.

Pan Li and Olgica Milenkovic, ``Submodular Hypergraph: $p$-Laplacian, Cheeger Inequalities and Spectral Clustering,'' ICML, 2018.

Pan Li and Olgica Milenkovic, ``Inhomogenous Hypergraph Clustering with Applications,'' NeurIPS, 2017.