Summary
Samuel Sohn is a software engineer with 11 years of experience bridging academic research and applied engineering, now working at Google in the New York City area. He holds a PhD-focused background from Rutgers where he led published machine-learning work on crowd flow and environment representations (ECCV 2020) and built cognitive models of navigation informed by psychology. At ETH Zurich he developed an information-theoretic architecture that fuses spatial, visual, crowd, and memory signals for agent decision-making, and previously contributed to real-time systems, VR validation studies, and autonomous-driving research at Motional.ai and Amazon. He combines deep expertise in ML, cognitive science, and simulation with hands-on software development for production research systems, and often translates human-centric experimental insights into scalable models. An understated strength is his track record mentoring and teaching—guiding students from elevator pitches to conference publications—so he brings both rigorous research judgment and an ability to communicate complex ideas to diverse teams.
11 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (Ph.D) Computer Science, Doctor of Philosophy (Ph.D) Computer Science at Rutgers University