About
Pan Li is an Assistant Professor in Electrical and Computer Engineering at Georgia Tech's College of Engineering. His research develops expressive machine learning models for graph-structured data, focusing on graph neural networks, geometric deep learning, and AI applications in scientific domains. He holds a PhD from University of Illinois Urbana-Champaign.
Research bridges theoretical foundations with scalable implementations for large graphs. Recent work includes equivariant architectures, hypergraph diffusion operators, and unsupervised combinatorial optimization. Recognitions include NSF CAREER Award and best paper awards.
- NSF CAREER Award (2023)
- Learning on Graph Conference Best Paper (2022)
- Sony Faculty Innovation Award (2021)
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