David MedinaPhD student, Department of Computational and Applied Mathematics, Rice University
Background and research interests
David obtained a Bachelor’s degree in Mathematics from The University of Texas-Pan American in 2011. He double-majored in Mathematics and Computer Science which led him to apply to the Computational and Applied Mathematics Department at Rice University. Due to his inclination in the computational aspect of Applied Mathematics, David began his PhD research in parallel algorithms for computational fluid dynamics under the advisement of Professor Tim Warburton.
David’s research involves high-performance numerical simulations for fluid flow using high-order spectral element methods in scalable GPU frameworks. He is currently working with incompressible Navier-Stokes (INS) equations and some modifications to the elliptic PDEs derived from the splitting scheme used to solve these INS equations. His projects with GPU-based computing involve hydrocarbon recovery, computer guided assistance in thermal therapy, and reactor simulations.
David is proficient in C/C++, Java, and Python and has experience in parallel computing using OpenMP and MPI for traditional CPU-based clusters and GPGPU programming languages (CUDA, OpenCL).
Apart from research, David enjoys learning about computer architecture, networking and other programming interests such as new languages or practices (especially tips/tricks in Linux, bash, Emacs, etc. for ergonomic purposes!)