About
I am the Morton E. Gurtin Assistant Professor of Applied Mathematics in the Division of Applied Mathematics at Brown University. I work on numerical methods for partial differential equations (PDEs), scientific machine learning, and PDE-constrained optimization.
Research Highlight: See this press release about my work on machine learning and black holes!
Short Bio: Before coming to Brown, I was a postdoctoral researcher at the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory. Before that, I was a postdoc at the Institute for Computational and Experimental Research in Mathematics. Before that, I was a postdoc at the Chair of Numerical Analysis at the Technical University of Munich, where I was supervised by Barbara Wohlmuth. Before that, I was a Ph.D. student at the Oden Institute for Computational Engineering & Sciences, where I was supervised by Leszek Demkowicz.
In The News!
I was selected as one of Popular Science’s “Brilliant 10” early career researchers of 2023
Current Research Funding
A.P. Sloan Research Fellowship in Mathematics 2025–2026
DOE SC Early Career Research Program 2023–2028 REASON-3D: Randomized, Entropic, Adaptive, and Scalable Optimization for Non-Intrusive Data-Driven Design
NSF Computational and Data-Enabled Science and Engineering 2024–2027 Data-Driven Discovery of Neural ODE Dynamics, Astrophysical Models, and Orbits (Neural ODE DynAMO)