Niklas Reinhardt

PHD student at Heidelberg University. Working on Statistical Learning Theory in Infinite Dimensions.

I am a third-year PhD student at Heidelberg University in the group of Jakob Zech. I studied mathematics and physics at Heidelberg University and KIT, specializing in numerical analysis and cosmology. My current research focuses on developing and analyzing machine learning architectures that act as surrogate models for (infinite-dimensional) maps. I work at the intersection of scientific computing, statistics, and machine learning. In particular, I implement and analyze so-called operator learning architectures to solve parameter-dependent partial differential equations.