Theme: Optimization, machine learning and statistical methods

It is of a societal interest to develop methods to secure models by design at training time, to audit the compliance of models already deployed online, and to scout out where AI is thwarting our trust. ARTISHAU targets the secondary properties of machine learning algorithms in a hostile environment due to the presence of an attacker.

Permanent Staff

• Teddy Furon, Researcher (DR), Inria centre at Rennes University, Team leader
• Charly Faure, DGA
• Eva Giboulot, Research Fellow, Inria centre at Rennes University
• Ewa Kijak, Associate Professor (HDR), University of Rennes
• Erwan Le Merrer, Researcher (HDR), Inria centre at Rennes University

Non-permanent members

• Isabela Borlido Barcelos
• Timothée Chauvin
• Virgile Dine
• Gautier Evennou
• Jade Garcia Bourrée
• Enoal Gesny
• Augustin Godinot
• Quentin Le Roux