Published multiple papers, including: AMG with filtering: an efficient preconditioner for interior point methods in large-scale contact mechanics optimization, A scalable interior-point Gauss-Newton method for PDE-constrained optimization with bound constraints, Further analysis of multilevel Stein variational gradient descent with an application to the Bayesian inference of glacier ice models, Point spread function approximation of high rank Hessians with locally supported non-negative integral kernels, A strong maximum principle for nonlinear nonlocal diffusion equations, PyAlbany: A Python interface to the C++ multiphysics solver Albany, Hierarchical off-diagonal low-rank approximation of Hessians in inverse problems, with application to ice sheet model initialization.
Research Experience
Conducted research in various areas including contact mechanics, turbulence-driven mixing of fluids, nonlocal and nonlinear diffusion equations, localized sensitivity exploiting algorithms for inverse problems governed by continental-scale ice-sheet models, nonlinear shallow-water equations for tsunami wave modeling, and infinite symmetry groups of PDEs.
Education
Ph.D. in Applied Mathematics from the University of California, Merced, 2022, Advisor: Dr. Noemi Petra; B.S. in Physics and Applied Mathematics from California State University, Chico, 2016.
Background
Research Interests: Scalable algorithms for nonlinear optimization and nonlinear equations with underlying partial differential equation (PDE) problem structure; Professional Field: Applied Mathematics, Physics; Brief Introduction: Postdoctoral researcher at the Center for Applied Scientific Computing, Lawrence Livermore National Laboratory.
Miscellany
Personal Interests: Long hikes, playing tennis, practicing yoga, and skateboarding. Enjoys traveling, spending time outdoors, and experiencing vegan food.