Campus Directory

Division Baskin School of Engineering

Department/College/Unit Baskin School of Engineering
Applied Mathematics

Title Adjunct Professor

Affiliation Faculty

Faculty Type Adjunct Faculty

Areas of Expertise Mathematics
Computational Modeling
Atmospheric Science

Web Site

Primary Office Location Engineering Building 2
240B

Mail Stop Engineering

Biography, Education and Training

I am also an Adjunct Professor of Applied Mathematics at the University of California at Santa Cruz. I am also a Distinguished Professor and the Chair of Applied Mathematics at the Naval Postgraduate School.  At NPS, I am a founding member of the Scientific Computing group and director of the Center for Computational Mathematics. 

My research is in the general area of Scientific Computing. My current interests are: 1) continuous and discontinuous Galerkin methods for solving systems of nonlinear partial differential equations (see my book); 2) time-integration (e.g., multirate and implicit); 3) adaptive mesh refinement; 4) high-performance computing; and 5) entropy-stable/energy-preserving methods.  My group works on trying to answer the question of how can we construct complex computer models that run effectively on the world's fastest computers. However, my general research interest lies in real-world problems. To this end, I have been constructing numerical models in order to better capture the behavior of atmospheric and oceanic systems. These are the goals of the projects listed below.

My group has developed a general framework for time-integration and preconditioning strategies to increase the computational performance of systems of nonlinear hyperbolic partial differential equations.  Now that we have constructed such a framework, we are setting our sights on interesting applications in earth and space weather problems. In addition, my group has also been focusing on Large-Eddy Simulations (LES) to better understand the fine-scale structures of meteorological applications, such as tropical cyclones (i.e., hurricanes).  This work includes exploiting reduced order models, scientific machine learning, and high-performance computing on GPUs.