Leonidas John Guibas (born 1949) is a Greek-American computer scientist and the Paul Pigott Professor of Computer Science, and by courtesy Electrical Engineering, at Stanford University, where he heads the Geometric Computation Group. His research spans computational geometry, computer graphics, computer vision, machine learning and robotics, with contributions including foundational data structures, the earth mover's distance for image retrieval, Metropolis light transport and the PointNet architecture for deep learning on point clouds. He is a member of the National Academy of Sciences, the National Academy of Engineering and the American Academy of Arts and Sciences, and a Fellow of the ACM and the IEEE. He received the ACM SIGGRAPH Steven A. Coons Award in 2025.
Facts
AwardACM-AAAI Allen Newell Award 1 Connections
Credited
Source NIST Dictionary of Algorithms and Data Structures: red-black tree
In Field
Source Leonidas J. Guibas (Wikipedia)
Source Leonidas J. Guibas (Wikipedia)
Source Leonidas J. Guibas (Wikipedia)
Source Leonidas J. Guibas (Wikipedia)
In the Other Atlases
Nationality
Also in Geography Atlas: the nationality of this subject.
Sources
1. Wikidata: Leonidas J. Guibas
- Wikidata Q3229792, resolved via en.wikipedia pageprops (wave rule R-L)
- Wikidata Q3229792 P569 (date of birth)
View the SourceNIST Dictionary of Algorithms and Data Structures: red-black tree
NIST Dictionary of Algorithms and Data StructuresCredited: Red-Black Tree Algorithm, NoteQuote, Credited: Red-Black Tree Algorithm, Note
The red/black naming and explanation was given by Guibas and Sedgewick.
Leonidas J. Guibas (Wikipedia)
In Field: Computer Graphics, Lead
His research spans computational geometry, computer graphics, computer vision, machine learning, and robotics, with contributions including foundational data structures, the earth mover's distance for image retrieval, Metropolis light transport, and the PointNet architecture for deep learning on point clouds.
In Field: Computer Vision, Lead
His research spans computational geometry, computer graphics, computer vision, machine learning, and robotics, with contributions including foundational data structures, the earth mover's distance for image retrieval, Metropolis light transport, and the PointNet architecture for deep learning on point clouds.
In Field: Machine Learning, Lead
His research spans computational geometry, computer graphics, computer vision, machine learning, and robotics, with contributions including foundational data structures, the earth mover's distance for image retrieval, Metropolis light transport, and the PointNet architecture for deep learning on point clouds.
In Field: Robotics, Lead
His research spans computational geometry, computer graphics, computer vision, machine learning, and robotics, with contributions including foundational data structures, the earth mover's distance for image retrieval, Metropolis light transport, and the PointNet architecture for deep learning on point clouds.
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