Sam Green is a Ph.D. candidate in Computer Science, at the University of California, Santa Barbara. His research is focused on numerical and architectural optimizations for reinforcement learning, as well as visualization diagnostics for CNN-based RL policies. Prior to attending UCSB, Sam was a Senior Member of Technical Staff, at Sandia National Laboratories, where he gained five years of experience contributing to and leading cryptographic hardware assessment R&D. Sam holds a master's in Applied Math and a bachelor's in Computer Science from the University of Central Arkansas.