Peter Ouyang is a Senior Staff AI Scientist in San Diego who blends 11 years of applied machine learning experience with a deep theoretical physics background (PhD, Princeton). He has led production personalization and recommendation systems at Intuit, including a model serving millions of TurboTax users, and scaled PB‑level satellite imagery ingestion and segmentation pipelines for mapwith.ai at Facebook. Comfortable moving between research and engineering, he turns abstract mathematical ideas into robust data pipelines and user-facing ML products. His prior work in string theory and gauge/gravity duality informs a rigorous, principled approach to model design and problem formulation that often surfaces nonobvious structure in messy real-world data.
11 years of coding experience
6 years of employment as a software developer
Bachelor's degree, Physics, Bachelor's degree, Physics at Massachusetts Institute of Technology
Doctor of Philosophy (PhD), Physics, Doctor of Philosophy (PhD), Physics at Princeton University
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