Brendan Keith

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 Funding

DOE SC Early Career Research Program  2024–2028   REASON-3D: Randomized, Entropic, Adaptive, and Scalable Optimization for Non-Intrusive Data-Driven Design
OVPR Seed Award (Brown Internal)  2023   Data-Driven High-Order Accurate Fail-Safe Neural Topology Optimization for Plastic Deformation and Fracture
LLNL LDRD  2022–2024   Adaptive Sampling for Risk-Averse Design and Optimization

Other notes:

  • 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 be found here.