Michael brings a wealth of applied mathematics and machine learning expertise to the team.

He graduated with a "Diplôme d'ingénieur" (equivalent to a MS) in Applied Mathematics from École Polytechnique in France, laying a solid foundation for his deep learning endeavors.

His academic journey culminated at Columbia University with an M.S. in Data Science, where he focused on advanced deep learning applications. As part of his graduate research, he explored AI for drug discovery, specifically enhancing question-answering systems on knowledge graphs to facilitate breakthroughs in healthcare.

Michael's previous professional experience includes a role at Feedly as an NLP Engineer. There, he was instrumental in developing sophisticated Named Entity Recognition models aimed at identifying malware and threat actors mentions in online articles, showcasing his adeptness in tackling complex challenges.