In this talk, an entirely new class of high-order numerical algorithms for computational fluid dynamics is introduced. The new method is based on the Gaussian Processes (GP) modeling that generalizes the Gaussian probability distribution. The new approach is to adopt the idea of the GP prediction technique which utilizes the covariance kernel functions and use it to reconstruct high-order approximations for computational simulations. The new GP high-order method is proposed as a new numerical high-order formulation, alternative to the conventional polynomial-based approaches.

Bio: Dongwook Lee is an associate professor of the Applied Mathematics Department at the University of California, Santa Cruz. Dongwook’s research interests emphasize on developing numerical schemes of high-order Godunov shock capturing methods for computational magnetohydrodynamics (MHD) and gas dynamics using explicit and implicit time integration algorithms on large-scale computing architectures. Prior to joining to the current position at UC Santa Cruz, he was an applied mathematician at the Flash Center for Computational Science at the University of Chicago. He was the main code architect of the unsplit hydrodynamics and magnetohydrodynamics solvers in FLASH.