Citizenship : Swiss, French
Birth date : 10.01.1972
He is Full Professor in the department of Computer Science at the University of Geneva, and Adjunct Professor in the School of Engineering of the École Polytechnique Fédérale de Lausanne. He has published more than 80 papers in peer-reviewed international conferences and journals.
He is Associate Editor of the IEEE Transactions on Pattern Analysis and Machine Intelligence, serves as Area Chair for NeurIPS, AAAI, and ICCV, and in the program committee of many top-tier international conferences in machine learning and computer vision. He is member of the Electrical Engineering Doctoral Program Committee at EPFL, and was or is expert for multiple funding agencies.
He is the inventor of several patents in the field of machine learning, and co-founder of Neural Concept SA, a company specializing in the development and commercialization of deep learning solutions for engineering design.
His main research interest is machine learning, with a particular focus on computational aspects and small sample learning.
Fields of expertise
Teaching & PhD
Electrical and Electronics Engineering
PhD StudentsCourdier Evann Pierre Guy, Dimitriadis Nikolaos, Janbakhshi Parvaneh, Johari Seyed Mohammad Mahdi, Kabil Selen Hande, Katharopoulos Angelos, Marelli Francois Thierry M, Matoba Kyle Michael, Pagliardini Matteo, Pannatier Arnaud, Shajkofci Adrian, Sivaprasad Prabhu Teja, Srinivas Suraj, Vyas Apoorv,
Past EPFL PhD StudentsAli Karim , Bagautdinov Timur , Baqué Pierre Bruno , Ben Shitrit Horesh Beny , Berclaz Jérôme , Canévet Olivier , Chavdarova Tatjana , Dubout Charles , González Serrano Germán , Jose Cijo , Lefakis Leonidas , Newling James Peter , Suditu Nicolae , Tulyakov Stepan ,
The course aims at providing an overview of existing processings and methods, at teaching how to design and train a deep neural network for a given task, and at providing the theoretical basis to go beyond the topics directly seen in the course.
It will touch on the following topics:
- What is deep learning, introduction to tensors.
- Basic machine-l