Raimund Seidel
Raimund G. Seidel is a German and Austrian theoretical computer scientist and an expert in computational geometry.
Seidel was born in Graz, Austria, and studied with Hermann Maurer at the Graz University of Technology.[1] He received his Ph.D. in 1987 from Cornell University under the supervision of John Gilbert.[2] After teaching at the University of California, Berkeley, he moved in 1994 to Saarland University.[3] In 1997 he and Christoph M. Hoffmann were program chairs for the Symposium on Computational Geometry. In 2014, he became director of the Leibniz Center for Informatics at Schloss Dagstuhl.[4]
Seidel invented backwards analysis of randomized algorithms and used it to analyze a simple linear programming algorithm that runs in linear time for problems of bounded dimension.[5] With his student Cecilia R. Aragon in 1989 he devised the treap data structure,[6][7] and he is also known for the Kirkpatrick–Seidel algorithm for computing two-dimensional convex hulls.[8]
References
- ↑ Profile in program for conference on significant advances in computer science, Graz University of Technology, 2007.
- ↑ Raimund G. Seidel at the Mathematics Genealogy Project.
- ↑ Profile at the Multimodal Computing and Interaction cluster, Saarland University.
- ↑ Internationally renowned informatics center names new Scientific Director, Schloss Dagstuhl, March 30, 2014, retrieved 2014-05-06.
- ↑ Seidel, R. (1991), "Small-dimensional linear programming and convex hulls made easy", Discrete & Computational Geometry 6 (1): 423–434, doi:10.1007/BF02574699.
- ↑ Aragon, Cecilia R.; Seidel, Raimund (1989), "Randomized Search Trees", Proc. 30th Symp. Foundations of Computer Science (FOCS 1989), Washington, D.C.: IEEE Computer Society Press, pp. 540–545, doi:10.1109/SFCS.1989.63531, ISBN 0-8186-1982-1
- ↑ Seidel, Raimund; Aragon, Cecilia R. (1996), "Randomized Search Trees", Algorithmica 16 (4/5): 464–497, doi:10.1007/s004539900061.
- ↑ Kirkpatrick, David G.; Seidel, Raimund (1986), "The ultimate planar convex hull algorithm", SIAM Journal on Computing 15 (1): 287–299, doi:10.1137/0215021.