Victor Quétu

I am currently an AI Research Scientist at Thales cortAIx-Labs, focusing on Explainable AI (XAI), developing methods to make deep learning models more transparent, interpretable, and trustworthy for real-world deployment.

I recently completed my PhD at Télécom Paris, Institut Polytechnique de Paris. Under the supervision of Gaël Richard and Enzo Tartaglione, my research focused on the development of efficient inference approaches for deep learning models, with the goal of enhancing computational efficiency and enabling real-world deployment.

I hold an engineering degree from École Nationale Supérieure de l’Électronique et de ses Applications. Prior to my PhD, I interned at Thales under the supervision of Serdar Şahin, where I designed and implemented deep learning algorithms to enhance the performance-complexity trade-off of the receiver in communication systems.