Andrew Nam is a Senior Applied Scientist at Microsoft with a decade of experience at the intersection of cognitive science and machine learning, specializing in reinforcement learning post‑training and integrative memory systems for large language models. He earned a PhD in Psychology from Stanford where he studied compositional, systematic, and symbolic reasoning as emergent properties in humans and neural networks, and then probed mechanistic interpretability through causality and information theory as a postdoc at Princeton's AI Lab. His background blends hands‑on engineering—systems and tooling work at Salesforce and SpaceX—with deep theoretical research on abstract reasoning, transfer, and memory in neural models. Andrew has collaborated with leading labs including Yoshua Bengio’s group at Mila, tying generative and attractor dynamics to semantic memory models. Colleagues describe him as someone who moves fluidly between building reliable production services and uncovering mechanistic hypotheses about how models think, often bringing experimental rigor from psychology into ML practice.
10 years of coding experience
4 years of employment as a software developer
Bachelor's degree Computer Science, Bachelor's degree Computer Science at University of California, Berkeley
Doctor of Philosophy - PhD Psychology, Doctor of Philosophy - PhD Psychology at Stanford University
Contributions:2 PRs, 77 pushes, 10 branches in 3 months
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Andrew Nam - Senior Applied Scientist at Microsoft