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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.


Fast multipole preconditioners for sparse matrices arising from elliptic equations
Ibeid Huda, Yokota Rio, Pestana Jennifer, Keyes David
Computing and Visualization in Science, (2017)
Refined saddle-point preconditioners for discretized Stokes problems
Pearson John W., Pestana Jennifer, Silvester David J.
Numerische Mathematik, (2017)
GMRES convergence bounds for eigenvalue problems
Freitag Melina A., Kürschner Patrick, Pestana Jennifer
Computational Methods in Applied Mathematics, (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)
Investigation of a polynomial matrix generalised EVD for multi-channel Wiener filtering
Corr Jamie, Pestana Jennifer, Weiss Stephan, Redif Soydan , Moonen Marc
50th Asilomar Conference on Signals, Systems and Computers, (2016)
Preconditioning for nonsymmetry and time-dependence
McDonald Eleanor, Hon Sean, Pestana Jennifer, Wathen Andrew
23rd International Conference on Domain Decomposition Methods, pp. 1-11, (2016)

more publications


Mathematics and Statistics
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