Sam Foreman

Sam Foreman

Postdoctoral Appointee


Sam Foreman is a computational scientist with a background in high energy physics, currently working as a postdoc in the ALCF. 

He is generally interested in the application of machine learning to computational problems in physics, particularly within the context of high performance computing.

Sam's current research focuses on using deep generative modeling to help build better sampling algorithms for simulations in lattice gauge theory.

Sam's Personal website: