Lei Li
School of Data Science, University of Virginia

102 Cresap, Rm. 102
Charlottesville, VA 22903
Lei Li is a tenure-track Assistant Professor of Data Science at the University of Virginia. Before joining UVA in 2025, he was a postdoctoral researcher at the Technical University of Munich, working with Prof. Angela Dai, and at École Polytechnique / Inria, working with Prof. Maks Ovsjanikov. Lei received his PhD in Computer Science and Engineering (2020) from the Hong Kong University of Science and Technology, and his BEng in Software Engineering (2014) from Shandong University. His PhD thesis advisor was Prof. Chiew-Lan Tai. Lei’s research interests are in computer vision and computer graphics, with a focus on advancing machine spatial intelligence to perceive, understand, and interact with the 3D world.
Open Positions
Our Spatial AI Lab (SAIL) is always looking for highly motivated PhD students and postdocs to work on impactful research at the intersection of computer vision, computer graphics, and artificial intelligence. If you are interested in joining us, please fill out this form. More application details can be found in the openings flyer. PhD applicants must also apply to the UVA School of Data Science PhD Program.
News
08.2025 | I joined the School of Data Science at the University of Virginia as a tenure-track Assistant Professor. |
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08.2025 | I will serve as an Area Chair for CVPR 2026. |
06.2025 | Our work DiffuMatch: Category-Agnostic Spectral Diffusion Priors for Robust Non-rigid Shape Matching has been accepted by ICCV 2025. |
06.2025 | Our work MeshPad: Interactive Sketch-Conditioned Artist-Designed Mesh Generation and Editing has been accepted by ICCV 2025. |
03.2025 | I was invited to serve as a member of the program committee for Pacific Graphics 2025. |
more... |
Selected Publications
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ECCV
To Supervise or Not to Supervise: Understanding and Addressing the Key Challenges of Point Cloud Transfer LearningIn European Conference on Computer Vision 2024 -
CVPR
Generalizable Local Feature Pre-training for Deformable Shape AnalysisIn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023 -
NeurIPS
Learning Multi-resolution Functional Maps with Spectral Attention for Robust Shape MatchingIn Neural Information Processing Systems 2022 -
CG&A
Fast Sketch Segmentation and Labeling with Deep LearningIEEE Computer Graphics and Applications 2018