Summary
Nhat Le is a research scientist with 11 years of experience translating statistical rigor into production-ready machine learning systems for computational neuroscience and biotech. He holds a PhD from MIT and has led interdisciplinary teams building cloud-native pipelines that process tens of gigabytes of imaging and behavioral data per day, enabling first-authored publications and conference presentations. His work spans state-space and recurrent neural models for behavioral prediction, explainable AI in startup settings, and scalable ETL on AWS that materially reduced query times and storage. Now at Meta after senior roles at PathAI, he combines academic depth with product-oriented delivery, routinely bridging neuroscience experiments and deployed analytics. A detail that often surprises collaborators: he built automated neuro-experiment tooling early in his career (e.g., song-syllable detection for zebra finch perturbations), showing a long-running knack for turning lab methods into reproducible software.
12 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD, Brain and Cognitive Sciences and Statistics, 5.0/5.0, Doctor of Philosophy - PhD, Brain and Cognitive Sciences and Statistics, 5.0/5.0 at Massachusetts Institute of Technology
California Institute of Technology
National Junior College
English, Vietnamese, French