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
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)