Summary
Alexandre Popoff is a data scientist and ML researcher with a strong foundation in physics, chemistry, and nanoscience, blending rigorous scientific training with practical, production-ready ML applications. He currently serves as a Research Scientist in Machine Learning at Philips and is a Board Member (Member-At-Large) of the Society for Mathematics and Computation in Music, underscoring his commitment to interdisciplinary work. His work spans deep learning for medical imaging, industrial and marketing ML applications, and the mathematical formalization of music, with a focus on data visualization and scalable tools (Python, Spark, d3.js). Earlier at Saint-Gobain Recherche, he led data science initiatives and drove analytical solutions across production and marketing, applying new ML techniques to industrial challenges. An ESPCI engineer with a Master in Organic Chemistry and a PhD in Organic Chemistry / Nanosciences, he brings a rare blend of domain expertise and computational fluency to his teams. Based in the Greater Paris area, he brings nine years of experience to deliver impactful ML-driven insights across science, industry, and music.
9 years of coding experience
5 years of employment as a software developer
Diplôme d'Ingénieur ESPCI, Spécialisation Chimie, Diplôme d'Ingénieur ESPCI, Spécialisation Chimie at Ecole supérieure de Physique et de Chimie industrielles de la Ville de Paris
Doctor of Philosophy (PhD), Organic Chemistry / Nanosciences, Doctor of Philosophy (PhD), Organic Chemistry / Nanosciences at Université Paris VI - Commissariat à l'Energie Atomique
Master 2, Organic Chemistry, Master 2, Organic Chemistry at Université Pierre et Marie Curie (Paris VI)
French, English, Swedish, modern arabic, Hindi, Russian