PhD candidate at Caltech
I am a third year PhD candidate in the Department of Computing + Mathematical Sciences at Caltech. My research interests lie at the intersection of computational science and applied mathematics. In the past, I've have done research on learning the structure of dynamical systems from data and scientific computing. Currently, I work on learning homogenized constitutive models, which is a setting where partial differential equations describe how multiscale materials respond to forcing. At Caltech, I work in the group of Professor Andrew Stuart.
In Summer 2021, I worked at at Sandia National Labs researching quantum inference algorithms. I'm currently collaborating with a group at Lawrence Livermore National Labs on reduced order modeling methods.
I am a recipient of the Department of Energy Computational Science Graduate Fellowship. I received my SB degree from MIT in Mathematics with minors in computer science and mechanical engineering in 2020.
Recent: I'm at ICIAM! Check out the minisymposia schedule I made here.
Check out our new arXiv preprint on learning homogenization in the presence of discontinuous PDE coefficients!
trautner (at) caltech (dot) edu