Jennifer Pestana

Dr Jennifer Pestana is a Senior Lecturer in the Department of Mathematics and Statistics at the University of Strathclyde, Faculty of Science. She has been a faculty member since 2015 and is actively involved in research and academic leadership. She is a principal investigator on multiple grants and serves as an editor for SIAM publications.

Education:

• DPhil, University of Oxford, 2012
• Postdoctoral positions: University of Manchester, University of Oxford

Her research centers on numerical linear algebra and its applications in scientific computing. She investigates the convergence of Krylov subspace methods, develops preconditioners for specific applications, and explores the use of tropical algebra for matrix pre-scaling. Current projects involve fast solvers for fractional diffusion and analysis in broadband signal processing. Her work bridges theoretical numerical analysis with practical computational challenges.

The recent publications reflect a strong focus on iterative methods, matrix analysis, and signal processing. Common themes include Toeplitz matrices, eigenvalue decomposition, preconditioning, and covariance estimation, demonstrating her expertise in both algorithmic development and application-driven numerical methods.

Scientific Awards:

• Best Student Paper Award (2018)

Dr Pestana actively supervises students and leads research projects, including EPSRC-SFI and Strathclyde ISP Joint PhD initiatives. She has secured significant funding for work on Krylov methods and efficient solvers. Her professional service includes organizing major conferences such as the Biennial Conference on Numerical Analysis and serving on program committees, including for the International Linear Algebra Society. She is also an invited speaker and visiting researcher, demonstrating national and international recognition.

She is involved with research teams focused on numerical analysis and scientific computing, contributing to collaborative efforts in developing novel preconditioned iterative solvers. Her lab and project groups work on both theoretical and applied aspects of linear algebra in PDEs and signal processing.