Title:  Machine learning models for biophysics.
Abstract:  Protein interactions govern most physiological processes. Predicting the structure of protein interactions is an important open question, as is understanding the impacts of mutations on the strength of association. I will discuss the use of machine learning to develop predictive models for these questions. In addition, recent work on generative adversarial networks for protein structure design will be presented.