Summary
Agnes M is a Sorbonne-trained PhD engineer with a decade of experience researching and teaching at the intersection of deep learning, information retrieval, NLP and reinforcement learning. Her thesis advanced understanding of Transformer-based models for query suggestion and introduced a user-machine interaction framework now cited in IR venues, pairing strong theoretical work with applied experiments on foundation models (BERT, BART, GPT). As a freelance consultant and trainer based in Paris, she helps design responsible AI projects that account for environmental, social and ethical considerations, translating research insights into practical systems. Her background spans industry R&D (Deezer, computer vision and pricing startups) and extensive teaching across university-level ML and recommender courses, giving her a rare blend of research rigor, product-minded experimentation and pedagogy.
11 years of coding experience
1 year of employment as a software developer
Classe préparatoire aux Grandes Ecoles, Mathematics, Classe préparatoire aux Grandes Ecoles, Mathematics at ENCPB
Master of science (M2), Machine Learning, Master of science (M2), Machine Learning at Pierre and Marie Curie University
Machine Learning, Machine Learning at MOOC : Stanford University, Johns-Hopkins, fast.ai
Master's degree, Mechanical-Electrical Engineering, Master's degree, Mechanical-Electrical Engineering at Ecole spéciale des Travaux publics, du Bâtiment et de l'Industrie
Baccalauréat in Science, Good awarded, Baccalauréat in Science, Good awarded at Victor Duruy
English, German, Italian, French