Summary
Thanard Kurutach is a Member of Technical Staff in the San Francisco Bay Area with nine years of experience building and researching machine learning and AI systems, most recently transitioning from senior research at Cruise to a role at ReflectionAI. He holds a PhD in Computer Science from UC Berkeley, where his thesis focused on learning, planning, and acting with models under advisors Pieter Abbeel and Stuart Russell, and has broader research stints at Google Brain and MIT. His work spans model-based reinforcement learning, hierarchical visual models, and practical ML engineering—shipping prototypes to production in automotive and robotics contexts. Beyond publications, he has a track record of accelerating inference and probabilistic modeling (e.g., faster Gibbs sampling and dynamic clustering) and applying these ideas in applied settings like solar prediction and mobile voice recognition. Passionate about AI, sports, and people, he blends deep theoretical grounding with product-minded implementation and mentorship. An underappreciated detail: he has repeatedly bridged academia and industry, turning complex probabilistic methods from his PhD into real-world systems.
8 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (PhD) Computer Science, Doctor of Philosophy (PhD) Computer Science at University of California, Berkeley
Bachelor of Science (B.S.) Electrical Engineering and Computer Science; Mathematics, Bachelor of Science (B.S.) Electrical Engineering and Computer Science; Mathematics at Massachusetts Institute of Technology
English, Thai