Associate Professor
Joined School 2001
BSc (University of British Columbia),
PhD (University of Toronto)
| mwg@uwaterloo.ca | |
| Web | http://www.cs.uwaterloo.ca/~mwg |
| Voice | 519-888-4567 x36582 |
| Fax | 519-885-1208 |
|
| Mark Giesbrecht
Associate Professor Joined School 2001 BSc (University of British Columbia),
|
Professor Giesbrecht's research interests are in the area of computer algebra, algebraic algorithms and complexity. He is a member of the Symbolic Computation Group in Waterloo, a founding member of the Ontario Research Centre for Computer Algebra with Waterloo and Western Ontario. He is an active participant in the computer algebra research community and has served as the Chair of the ACM Special Interest Group on Symbolic and Algebraic Computation. His work focuses on many aspects of computer algebra, from the design and complexity analyses of fundamental algorithms for matrices and polynomials, to algorithms for approximate or symbolic-numeric problems, to the design of efficient generic software libraries for symbolic computation.
With his graduate students and colleagues, some of the research topics he has addressed are as follows: algorithms for sparse polynomials and matrices; symbolic linear algebra and solving systems of linear diophantine equations; computing with associative algebras and modular group representations; symbolic-numeric computation, including approximate polynomial factorization and approximate sparse interpolation. Professor Giesbrecht is a principal investigator in the LinBox library group, which is designing a C++ template library for symbolic linear algebra with very large, sparse matrices. See http://www.linalg.org.
NSERC Synergy Innovation Award for Maplesoft & Symbolic Computation Group (2004)
Professor Giesbrecht maintains an active industrial collaboration is with Waterloo Maple Inc. He spent his most recent sabbatical in the MMRC at the Chinese Academy of Science in Beijing, and at the Laboratoire LIP, ENS Lyon.
J. von zur Gathen, M. Giesbrecht and K. Ziegler, Composition collisions and Projective Polynomials, Proceedings of ISSAC 2010, pp. 123-130
M. Giesbrecht, G. Labahn and W-s. Lee, Symbolic-numeric sparse interpolation of multivariate polynomials. Journal of Symbolic Computation. Volume 44, 2009, pp. 943-959, 2009.
M. Giesbrecht and D. Roche. On Lacunary Polynomial Perfect Powers. Proceedings of ACM International Symposium on Symbolic and Algebraic Computation (ISSAC), 2008.
W. Eberly, M. Giesbrecht, P. Giorgi, A. Storjohann, and G. Villard. Faster Inversion and Other Black Box Matrix Computations Using Efficient Block Projections. Proceedings of ACM International Symposium on Symbolic and Algebraic Computation (ISSAC), pp. 143-150, 2007.
W. Eberly and M. Giesbrecht. Efficient decomposition of separable algebras. Journal of Symbolic Computation, 37(1):35-81, 2004.
David R. Cheriton School of Computer Science
University of Waterloo
Waterloo, Ontario, Canada N2L 3G1
Tel: 519-888-4567 x33293
Fax: 519-885-1208
Contact | Feedback: cs-webmaster@cs.uwaterloo.ca | David R. Cheriton School of Computer Science | Faculty of Mathematics
Last modified: Monday, 20-Dec-2010 14:30:01 EST
