Professor and Dean, Faculty of Mathematics

Research interests

Professor Giesbrecht's research interests are in the area of computer algebra, algebraic algorithms and computational complexity. He is a member of the Symbolic Computation Group in Waterloo, and a founding member of the Ontario Research Centre for Computer Algebra with Waterloo and Western Ontario.

photo of Professor Mark Giesbrecht

He is an active participant in the computer algebra research community and has served as Program Committee Chair of the International Symposium on Symbolic and Algebraic Computation (ISSAC 2013) and the Chair of the ACM Special Interest Group on Symbolic and Algebraic Computation (ACM SIGSAM). 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.

Degrees and awards

BSc (British Columbia), MSc, PhD (Toronto)

ACM Distinguished Scientist (2013)

NSERC Synergy Innovation Award for Maplesoft & Symbolic Computation Group (2004)

Industrial and sabbatical experience

Professor Giesbrecht maintains an active industrial collaboration 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.

Representative publications

M. Elsheikh, M. Giesbrecht. Relating p-Adic eigenvalues and the local Smith normal form. Linear Algebra and It's Applications. Volume 481, 15 September 2015, Pages 330–349. 
M. Giesbrecht and M. Sub Kim. Computation of the Hermite form of a Matrix of Ore Polynomials. Journal of Algebra, Volume 376, 15 February 2013, Pages 341–362. 
M. Giesbrecht, D. Roche, and H. Tilak. Computing sparse multiples of polynomials. Algorithmica. Volume 64, Number 3, pp.454­480, 2012. 
M. Giesbrecht and D. Roche. Detecting lacunary perfect powers and computing their roots, Journal of Symbolic Computation, v. 46, pp1242-1259, 2011.
M. Giesbrecht and D. Roche, Interpolation of shifted-lacunary polynomials. Computational Complexity. Volume 19, No 3., pp. 333-354, 2010. 
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.
University of Waterloo
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