Summary
Michael Lopez-brau is an AI Engineer and cognitive scientist with 11 years of experience building data-driven systems and research-backed models that bridge human behavior and production ML. He earned a PhD in Computational Cognitive Science from Yale, where he developed novel Bayesian models that matched human performance, ran large-scale behavioral experiments, and published multiple first-author papers. In industry he architects end-to-end agentic RAG pipelines and custom speech-to-text systems—recently shipping a scalable Azure-based tool that extracts insights from thousands of hours of proprietary audio and video for medical strategists. Comfortable across the stack, he combines Python/FastAPI backends, Azure AI Search, and Nuxt frontends to move research artifacts into reliable products. He brings unusual depth in experimental design and HPC benchmarking (500GB+ datasets), making him adept at translating complex statistical ideas into actionable insights for stakeholders. Based in San Diego, he pairs rigorous academic methods with practical engineering to solve domain-specific problems in health and cognition.
11 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy, Computational Cognitive Science, Doctor of Philosophy, Computational Cognitive Science at Yale University
Bachelor of Science, Electrical Engineering, Bachelor of Science, Electrical Engineering at University of Central Florida
English, Spanish