Victoria E. Howle
Department of Mathematics & Statistics
Texas Tech University

Office: Mathematics 117-D
Phone (voicemail only): (806) 834-8770
Phone (math department office): (806) 742-2566


Fall 2023:

Previous Courses


My research is in applied mathematics with a focus mainly on numerical linear algebra. My main research interests are currently in physics-based preconditioning for incompressible fluid flow problems, scalable preconditioners for implicit Runge-Kutta methods, and machine learning algorithms.

Preconditioning for incompressible fluid flow problems: Along with a number of collaborators, I have worked on developing and analyzing scalable preconditioners for Navier–Stokes simulations, including problems that are extensions to standard incompressible flow models. Many important scientific systems require solution of such extensions, whether by incorporating additional nonlinear effects or by coupling to other physical processes.

Scalable Preconditioners for Implicit Runge-Kutta Methods: Another research area has been investigating scalable preconditioners for implicit Runge-Kutta methods. Many important engineering and scientific systems require the solution of time-dependent PDE systems. Many of these sytems have specific stability needs in order to compute realistic solutions. Certain classes of implicit Runge-Kutta (IRK) methods provide this stability. However, one price of using IRK methods is the need to solve large linear systems at each time step, which can be quite expensive computationally. Preconditioning is necessary for these systems to be solved efficiently.




Background & Other Info

Non-Math Life

Current Students

Former Students & Postdocs

Some useful Links

Last updated: November 2023
Copyright © 2008-2023, Victoria Howle and Department of Mathematics & Statistics, Texas Tech University All rights reserved.