Leonidas J. Guibas
Leonidas Guibas | |
---|---|
Leonidas Guibas | |
Residence | U.S. |
Nationality | Greek-American |
Fields | Computer Science |
Institutions | Stanford University |
Doctoral advisor | Donald Knuth |
Leonidas John Guibas (Greek: Λεωνίδας Γκίμπας) is a professor of computer science at Stanford University, where he heads the geometric computation group and is a member of the computer graphics and artificial intelligence laboratories. Guibas was a student of Donald Knuth at Stanford, where he received his Ph.D. in 1976.[1] He has worked for several industrial research laboratories, and joined the Stanford faculty in 1984. He was program chair for the ACM Symposium on Computational Geometry in 1996,[2] is a Fellow of the ACM[3] and the IEEE,[4] and was awarded the ACM - AAAI Allen Newell Award for 2007 “for his pioneering contributions in applying algorithms to a wide range of computer science disciplines.“[5] He has Erdős number 2 due to his collaborations with Boris Aronov, Andrew Odlyzko, János Pach, Richard M. Pollack, Endre Szemerédi, and Frances Yao.[6] The research contributions he is known for include finger trees, red-black trees, fractional cascading, the Guibas–Stolfi algorithm for Delaunay triangulation, an optimal data structure for point location, the quad-edge data structure for representing planar subdivisions, Metropolis light transport, and kinetic data structures for keeping track of objects in motion.
References
- ↑ Leonidas John (Ioannis) Guibas at the Mathematics Genealogy Project.
- ↑ Program Committees from the Symposium on Computational Geometry, Computational Geometry Steering Committee.
- ↑ ACM Fellow award citation.
- ↑ 2012 Newly Elevated Fellows, IEEE, accessed 2011-12-10.
- ↑ ACM/AAAI Allen Newell Award Recognizes Leonidas Guibas for Algorithms Advancing CS Fields, ACM, 2008; "Guibas Receives ACM/AAAI Award for Algorithm Development", Dr. Dobb's, March 4, 2008.
- ↑ Erdős number project.
External links
- Guibas laboratory
- Detection of Symmetries and Repeated Patterns in 3D Point Cloud Data, videolecture by Guibas
- Publications at ACM Portal
- Publications at Google Scholar