Leonidas Guibas

Leonidas Guibas is the Paul Pigott Professor of Engineering and Professor (by courtesy) of Electrical Engineering at Stanford University's Department of Computer Science. He leads the Geometric Computation group and is affiliated with the Computer Graphics and Artificial Intelligence Laboratories. His research focuses on algorithms for sensing, modeling, and reasoning about the physical world, with expertise in computational geometry, robotics, sensor networks, and topological data analysis. Current work includes geometric modeling with point clouds, 3D reconstruction, and mobility data analysis. He holds prestigious awards including ACM Fellow (1999), Allen Newell Award (2008), and membership in the National Academy of Sciences (2022).

Education:

• PhD, Stanford University (1976)
• MS & BS, California Institute of Technology (1971)

Research Interests:

• Geometric and topological data analysis
• 3D reconstruction and 3D shape analysis
• Sensor networks and robotics
• Biological structure modeling
• Machine learning for geometric problems

Recent Articles Focus: Recent work emphasizes neural radiance fields (NeRF), dynamic Gaussian splatting, and physically plausible 3D shape generation. Publications span advancements in symmetry detection, articulated object manipulation, and multi-view video generation.

Awards & Honors:

• Fellow, ACM (1999)
• Allen Newell Award (2008)
• Fellow, IEEE (2011)
• Member, National Academy of Engineering (2017)
• Member, National Academy of Sciences (2022)

Advising & Teams: Advises doctoral and master's students on topics like geometric computing and robotics. Leads interdisciplinary teams at Stanford's ICME, HAI, and Woods Institute. Current advisees include Ian Huang, Boxiao Pan, and Colton Stearns.

Labs & Collaborations: Active in the Geometric Computation group and collaborates with the Stanford AI Lab. Works on projects funded by grants in robotics, computer vision, and computational biology.