About

I am an Assistant Professor 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 recent 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.

Current Research Grants

LDRD  2022–2024   Adaptive Sampling for Risk-Averse Design and Optimization (PI, $450,000/year)

Other notes:

• I still do finite element research! In fact, I’m an active MFEM developer. Check out our (growing) list of examples codes and miniapps here.
• This website has been tidied up a little bit. If you are interested in my old finite element work (2015-2020), short summaries can still be found here.