Antoine Debouchage is a PhD candidate in Applied Mathematics at Université Paris-Saclay and a Cifre researcher with 11 years of technical experience bridging machine learning, optimization, quantum computing and NLP. Trained at CentraleSupélec and ENS Paris-Saclay (MVA), he has shipped research-grade tooling and datasets for financial NLP, developed state-of-the-art fine-tuning pipelines (LoRA, 4-bit quantization), and authored novel pretraining methods for LLMs (AccLoRT) while interning at RIKEN. His background in tensor networks and quantum-inspired optimization informs efficient model compression and low-rank approaches used across his projects. Comfortable moving from theory to production, he has scraped and curated large-scale corpora, built internal NLP applications for institutions like Banque de France, and driven diversity-aware paraphrasing research at Reverso. Colleagues describe him as a mathematically rigorous engineer who repeatedly finds practical uses for advanced linear-algebraic insights in ML systems.
11 years of coding experience
1 year of employment as a software developer
MVA - Master 2 (M2) Mathématiques et informatique, MVA - Master 2 (M2) Mathématiques et informatique at ENS Paris-Saclay
Master 2 (M2), Master 2 (M2) at CentraleSupélec
Doctor of Philosophy - PhD Applied Mathematics, Doctor of Philosophy - PhD Applied Mathematics at Université Paris-Saclay
Baccalauréat Sciences de l'ingénieur, Baccalauréat Sciences de l'ingénieur at Lycée Louis Armand - Nogent-sur-Marne
MPSI/MP* ー Classe Préparatoire aux Grandes Écoles, MPSI/MP* ー Classe Préparatoire aux Grandes Écoles at Lycée Condorcet
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