Summary
Lorenzo Noci is a machine learning researcher and software engineer with eight years of experience and a strong focus on Bayesian inference and uncertainty estimation. He holds advanced degrees from ETH Zürich and Politecnico di Milano and has worked across Shanghai, Zurich and Luxembourg, contributing to both academia and industry. His recent roles include Applied Scientist at Amazon, a visiting PhD stint at Princeton ORFE, a brief research role at Apple, and a current Member of Technical Staff position at OpenAI, reflecting a trajectory from production ML systems to cutting-edge research. Lorenzo combines practical data engineering skills—processing hundreds of gigabytes with Python, Spark and Snakemake—with deep ML expertise from his PhD work, making him effective at turning probabilistic research into deployable solutions. An international profile and hands-on background in parsing and monitoring large cluster logs hint at an unusual blend of low-level systems fluency and probabilistic modeling.
8 years of coding experience
3 years of employment as a software developer
Bachelor's degree, Information Technology, Bachelor's degree, Information Technology at Tongji University
Tsinghua University Big Data Summer School, Tsinghua University Big Data Summer School at Tsinghua University
Maturità scientifica, Maturità scientifica at Liceo Scientifico Amedeo di Savoia Duca d'Aosta
Bachelor, Computer Science and Engineering, Bachelor, Computer Science and Engineering at Politecnico di Milano
Doctor of Philosophy - PhD, Machine Learning, Doctor of Philosophy - PhD, Machine Learning at ETH Zürich
Italian, English, Chinese