Léo Laugier is a machine learning researcher and engineer focused on using large language models to address real-world problems in online conversations, including toxicity mitigation, argument mining, and social media simulation. With a PhD in Math & Computer Science and eight years of experience across academia and industry, he built self-supervised text-to-text transformers like CAE-T5 and fine-tuned large models (e.g., OLMo-2 32B) to simulate and analyze Reddit discussions. His postdoctoral work at EPFL produced SAGESSE, an LLM-driven system that structures complex online arguments and demonstrates practical prototypes bridging research and product. Now at Google, he combines rigorous NLP foundations with hands-on model engineering for interdisciplinary teams. Notably, he has applied techniques from recommender explainability to conversational transformation—rephrasing aggression into politeness—highlighting a rare blend of social-science-aware ML and scalable model fine-tuning. He is based in the United States and maintains an active research portfolio and public website showcasing his work.
8 years of coding experience
3 years of employment as a software developer
Master of Engineering - MEng, Computer Science, Master of Engineering - MEng, Computer Science at University of California, Berkeley
BSc. and MSc. - Dipl. Ing., Electrical Engineering, Computer Science and Telecommunications, BSc. and MSc. - Dipl. Ing., Electrical Engineering, Computer Science and Telecommunications at CentraleSupélec
Doctor of Philosophy - PhD, Mathematics and Computer Science, Doctor of Philosophy - PhD, Mathematics and Computer Science at Institut Polytechnique de Paris
Contributions:1 PR, 33 pushes, 3 branches in 6 years 11 months
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