Summary
Michael Rawson is a scientist and machine learning researcher with 14 years of experience focused on automated reasoning and automated theorem proving. Currently a Scientist at Amazon and completing a PhD in applied mathematics and statistics, he bridges rigorous academic research with applied industry work in formal methods and ML. His background includes an MS in Mathematics and Computer Science from NYU and a history as a research associate in automated reasoning, giving him deep expertise in probabilistic and symbolic techniques. Known for turning complex theoretical ideas into practical tooling, he combines theorem-proving insights with data-driven models to improve automation in reasoning systems. Based in Seattle, he brings a rare mix of long-standing engineering experience and fresh doctoral-level research, often exploring less obvious intersections between statistical learning and formal proof systems.
14 years of coding experience