Summary
Rafael Stern is an associate professor and quantitative researcher based in São Paulo with a decade of experience at the intersection of statistics, law, and machine learning. With a PhD in Statistics from Carnegie Mellon and dual undergraduate training in law and statistics, he applies jurimetrics, Bayesian decision theory, and ML to inform legal and policy decisions. He holds faculty positions at both Universidade de São Paulo and Universidade Federal de São Carlos, blending rigorous academic research with practical teaching experience dating back to Carnegie Mellon. Rafael’s work is characterized by translating complex probabilistic models into decision-ready insights for legal contexts—an uncommon blend that makes him fluent in both statutory reasoning and formal uncertainty quantification.
10 years of coding experience
Colégio Bandeirantes
BA, Law, BA, Law at Pontifícia Universidade Católica de São Paulo
MS, Statistics, MS, Statistics at USP - Universidade de São Paulo
PhD, Statistics, PhD, Statistics at Carnegie Mellon University