Summary
Pierre Lepagnol is a Data Science Researcher and Consultant based in Paris with eight years of experience applying Python, deep learning, and computer vision to real-world problems. Currently at SCIAM and completing a PhD at Université Paris-Saclay/LISN, he blends academic rigor in NLP and AI with hands-on consulting and research. His background spans cybersecurity-focused neural network robustness work at the DGA, practical data-product development in banking, and advanced statistical training from French grandes écoles. Comfortable moving models from research to deployable solutions, he pairs probabilistic and deep-learning approaches to tackle noisy, security-sensitive datasets. Active on GitHub and rooted in cross-disciplinary mathematics and physics studies, he brings a quantitative mindset and an uncommon emphasis on model embarquabilité and robustness.
8 years of coding experience
1 year of employment as a software developer
PhD, Natural Language Processing / Artifical Intelligence, PhD, Natural Language Processing / Artifical Intelligence at Université Paris-Saclay
Magistere Degree in Statistic and Economic modelling, Math & Statistics, Magistere Degree in Statistic and Economic modelling, Math & Statistics at Université de Rennes I
Master Degree, Applied Mathematics, Statistics, Master Degree, Applied Mathematics, Statistics at Université Rennes 2
Licence Modélisation et Ingénieurie Mathématique, Mathématiques appliquées, Licence Modélisation et Ingénieurie Mathématique, Mathématiques appliquées at Université Paris 13
3rd class, 3rd class at Bethany school
Physique théorique et mathématique, Physique théorique et mathématique at Université Paris Cité
Baccalauréat, Scientifique, Baccalauréat, Scientifique at Lycée Notre-Dame Providence
French, English