Summary
Stanislas Morbieu is a data scientist and machine learning researcher based in Paris with 11 years of experience building production-ready data products and scalable big data platforms. He holds a PhD in Computer Science and specializes in text mining, embeddings and recommender systems, with a track record of designing semantic similarity models for short texts and incorporating temporal user behavior. At Kernix he combines research-led experimentation with engineering: architecting scalable pipelines, implementing recommender systems, and mentoring teams through tech and scientific watch. He has academic roots at LIPADE and Université Paris Descartes, where his PhD and teaching roles reinforced a rigorous approach to unsupervised learning and coclustering. Comfortable across the full data value chain, he pairs theoretical depth with hands-on Spark and big-data experience to move models from prototype to production. An understated strength is his focus on documenting and sharing knowledge—publishing internal articles and presentations to elevate team practices.
11 years of coding experience
Specializations: Data Science - Cloud Computing - Data Mining, Specializations: Data Science - Cloud Computing - Data Mining at Coursera
Master 2 (M2), Artificial Intelligence, Very good, Master 2 (M2), Artificial Intelligence, Very good at Université Paris Descartes
PhD, Computer Science, PhD, Computer Science at Université de Paris
Engineering School in Computer Science, Artificial Intelligence, Engineering School in Computer Science, Artificial Intelligence at ENSIIE - École Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise
French, English, German