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Dr Jennifer Pestana


Mathematics and Statistics

Personal statement

My primary research interests are numerical linear algebra and its application to problems in scientific computing. Most of my work has focused on understanding the convergence behaviour of Krylov subspace methods for solving linear systems, and on developing preconditioners for specific applications. I have also been involved in projects that apply ideas from tropical algebra to problems in numerical linear algebra, such as pre-scaling matrices before solving linear systems.

I have been a lecturer in the Department of Mathematics and Statistics since 2015. Prior to this I held postdoctoral positions at The University of Manchester and the University of Oxford. I obtained my DPhil from the University of Oxford in 2012.

My personal webpage can be found here.


GMRES convergence bounds for eigenvalue problems
Freitag Melina A., Kürschner Patrick, Pestana Jennifer
Computational Methods in Applied Mathematics Vol 18, pp. 203-222, (2018)
Preconditioning and iterative solution of all-at-once systems for evolutionary partial differential equations
McDonald Eleanor, Pestana Jennifer, Wathen Andy
SIAM Journal on Scientific Computing Vol 40, pp. A1012–A1033, (2018)
On the existence and uniqueness of the eigenvalue decomposition of a parahermitian matrix
Weiss Stephan, Pestana Jennifer, Proudler Ian K.
IEEE Transactions on Signal Processing, (2018)
Refined saddle-point preconditioners for discretized Stokes problems
Pearson John W., Pestana Jennifer, Silvester David J.
Numerische Mathematik Vol 138, pp. 331-363, (2018)
Fast multipole preconditioners for sparse matrices arising from elliptic equations
Ibeid Huda, Yokota Rio, Pestana Jennifer, Keyes David
Computing and Visualization in Science, (2017)
Null-space preconditioners for saddle point systems
Pestana Jennifer, Rees Tyrone
SIAM Journal on Matrix Analysis and Applications Vol 37, pp. 1103-1128, (2016)

more publications


Mathematics and Statistics
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