Numerical Linear Algebra

Researchers in Numerical Linear Algebra

      • Silmane Adjerid profile picture
      • Slimane Adjerid

        Professor Adjerid conducts research on developing new discontinuous finite element methods for solving partial differential equations. His interest was on studying the superconvergence properties of discontinuous Galerkin methods that can be used to estimate discretization errors. Lately he his working on high-order immersed finite elements for interface problems.

      • Christopher Beattie profile picture
      • Christopher Beattie

        The principal research interests of Professor Beattie are in the areas of scientific computing and large scale computational linear algebra, with an emphasis on iterative Krylov methods. His primary focus is on model reduction of large scale dynamical systems with a goal of developing practical and rigorous computational algorithms for efficient manipulation and simulation of systems arising from physical models frequently described by systems of partial differential equations.

      • Timothy Warburton profile picture
      • Tim Warburton

        Professor Warburton holds the John K. Costain Chair in the College of Science at Virginia Tech and is a faculty member of both the Department of Mathematics and the Computational Modeling and Data Analytics program. His research interests include developing new parallel algorithms and methods that are used to solve PDE based physical modes on the largest supercomputers.

      • Lizette Zietsman

        Professor Zietsman's research area covers the development and analysis of fundamental numerical algorithms arising in the study of stability, control and estimation of distributed parameter systems typical in structural control, fluid flow control, and thermal systems.

      • Jason R. Wilson

        Collegiate Assistant Professor Wilson teaches Math and CMDA classes. His research interests include large scale linear algebra, high performance computing, and the mathematical foundations of data science.