Jonathan Laurent

Karlsruhe, Baden-Württemberg, Germany

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Summary

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Rockstar

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Top School

Jonathan Laurent is a PhD researcher in computer science at Carnegie Mellon University with 11 years of experience spanning language design for LLM-enabled software, self-supervised theorem proving, safe controller synthesis, and causal analysis of biological systems. He blends deep theoretical work with practical engineering—evidenced by a fast AlphaZero implementation in Julia where he adapted MCTS into a working TicTacToe solver. His background includes hands-on roles at Darklang optimizing an OCaml codebase, research internships at Harvard Medical School and NASA Langley, and years teaching rigorous mathematics to top French engineering students. Comfortable across formal verification, machine learning, and systems engineering, he often connects formal methods to real-world safety and biological problems. Based in Karlsruhe, Germany, he brings an uncommon mix of proof-driven research and production-minded coding that accelerates trustworthy ML systems.

12 years of coding experience

Master's degree, Machine Learning (Master Vision Apprentissage), Master's degree, Machine Learning (Master Vision Apprentissage) at ENS Paris-Saclay

Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Ecole normale supérieure

PhD in Computer Science, PhD in Computer Science at Carnegie Mellon University

Classes préparatoires aux grandes écoles, MPSI / MP*, Classes préparatoires aux grandes écoles, MPSI / MP* at Lycée Louis-Le-Grand

French, English

Github Skills (6)

algorithm10

algorithms10

machine-learning10

deep-learning10

tensorflow9

python8

Programming languages (16)

C++CSSLeanTeXScalaJupyter NotebookFortranJulia

Github contributions (5)

jonathan-laurent/AlphaZero.jl

Sep 2019 - Jan 2023

A generic, simple and fast implementation of Deepmind's AlphaZero algorithm.

Role in this project:

Back-end Developer & ML Engineer

Contributions:3 reviews, 651 commits, 28 PRs in 3 years 4 months

Contributions summary:Jonathan implemented a specialized version of the Monte Carlo Tree Search (MCTS) algorithm for AlphaZero, a deep learning method. Their contributions involved modifying the MCTS framework, specifically adapting it for the AlphaZero algorithm. The user also integrated the results into a TicTacToe solver, providing a concrete demonstration of their work.

alphazerojuliamachine-learningdeep-learning

jonathan-laurent/jonathan-laurent.github.io

Feb 2018 - May 2026

Contributions:70 pushes, 2 branches in 8 years 4 months

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