Leonidas J. Guibas

Leonidas J. Guibas

Leonidas John Guibas 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.mathgenealogy|name=Leonidas John (Ioannis) Guibas|id=39940.] 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, [ [http://www.ams.stonybrook.edu/~jsbm/cg-steer/socg-chairs.txt Program Committees from the Symposium on Computational Geometry] , Computational Geometry Steering Committee.] is a Fellow of the ACM, [ [http://fellows.acm.org/fellow_citation.cfm?id=1283951&srt=all ACM Fellow award citation] .] 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.“ [ [http://www.acm.org/press-room/news-releases/newell-award-07/ ACM/AAAI Allen Newell Award Recognizes Leonidas Guibas for Algorithms Advancing CS Fields] , ACM, 2008; citation|title=Guibas Receives ACM/AAAI Award for Algorithm Development|journal=Dr. Dobb's|date=March 04, 2008|url=http://www.ddj.com/hpc-high-performance-computing/206901618.] He has Erdős number 2 due to his collaborations with Boris Aronov, Andrew Odlyzko, Janos Pach, Richard M. Pollack, Endre Szemerédi, and Frances Yao. [ [http://www.oakland.edu/enp/ Erdos number project] .] 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

External links

* [http://geometry.stanford.edu/member/guibas/ Guibas laboratory]


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