Mathis Gerdes

I work on non-perturbative problems in quantum field theory and related quantum systems, developing computational methods that combine machine learning with the symmetries, geometry, and constraints of the theory. More broadly, I am interested in both directions of the exchange: machine learning for physics, and the physics of machine learning.

Before my current position at MIT, I did my PhD at the University of Amsterdam with Miranda Cheng and Christoph Weniger.