PhD, University of Toronto
David Del Rey Fernández is an Assistant Professor at the University of Waterloo, Department of Applied Mathematics. Before joining the University of Waterloo, he was first a postdoctoral researcher and then a research scientist at NASA Langley Research Center and the National Institute of Aerospace.
His research interest is in developing efficient and robust numerical algorithms for the solution of partial differential equations based on novel numerical methods with provable properties, applicable to high-performance computing systems. David’s research is focused on developing the mathematics and algorithms for the efficient solution of a broad class of time-dependent partial differential equations in the context of mathematically rigorous numerical frameworks. In particular, the emphasis is on:1) robust numerical methods, 2) mesh adaptation, 3) approaches for dealing with geometric complexity and moving meshes, and 4) machine-learning algorithms for automation and increased efficiency.
- Numerical simulation of partial differential equations
- Mathematically robust schemes
- Summation-by-parts methods
- Continuous and discontinuous Galerkin schemes, finite difference schemes, etc.
- Mesh adaptation
- Machine learning for acceleration of scientific computing