Sylvain GIGAN

About Sylvain GIGAN

Sylvain Gigan is a well-known French academic and a co-founder of LightOn, a pioneering sovereign generative AI company in France. Within LightOn, he serves as Scientific Advisor and also sits on the company’s board of directors, contributing to the governance of a business that is now listed on Euronext Growth. His profile reflects the combination of world-class academic research and technology entrepreneurship. He is a full professor at the École polytechnique fédérale de Lausanne (EPFL), where he heads the IdePHICS laboratory, focused on Information, Learning and Physics. His research interests span statistical physics, machine learning, statistics, computer science, and computational optics. Before joining EPFL, he built a long academic career in France: he earned a PhD in statistical physics in 2002, became an associate professor at ESPCI Paris, and was later appointed full professor at Université Pierre et Marie Curie and École Normale Supérieure de Paris. His career demonstrates a strong scientific background shaped by leading French and international research institutions, including visiting roles at Berkeley, Duke, and Los Alamos. At LightOn, his contribution is closely tied to the company’s founding vision: turning advanced scientific expertise into practical generative AI and enterprise search solutions. As a scientist-advisor, he helps reinforce the technological credibility of the company, supports its R&D orientation, and ensures that innovation remains aligned with the highest standards in the sector. His role on the board also strengthens the governance profile of a company that emphasizes data privacy, sovereignty, and industrial-grade AI deployment. More broadly, Sylvain Gigan represents a rare combination of academic excellence, deep-tech expertise, and strategic involvement in a listed AI company. His background in leading universities and his position at LightOn make him a significant profile for understanding how advanced research can translate into entrepreneurial success in artificial intelligence.