Edition 2017

Stéphane Canu

Stéphane Canu is Professor of Data Science at INSA Rouen. He received a Ph.D. degree in System Command from  Comiègne University of Technology in 1986. He joined the faculty department of Computer Science at Compiegne University of Technology in 1987. He received the French habilitation degree from Paris 6 University. In 1997, he joined the Rouen Applied Sciences National Institute (INSA) as a full professor, where he created the information engineering department. He has been the dean of this department until 2002 when he was named director of the  computing service and facilities unit. In 2004 he join for one sabbatical year the machine learning group at ANU/NICTA (Canberra) with Alex Smola and Bob Williamson.  In the last five years, he has published approximately thirty papers in refereed  conference proceedings or journals in the areas of theory, algorithms and applications  using kernel machines learning algorithm and other flexible regression methods.  His research interests includes kernels machines, regularization, machine learning applied to signal processing, pattern classification, factorization for recommander systems and learning for context aware applications.

Lecture on the Overview of Deep Learning today

Soufiane Belharbi

Soufiane Belharbi is a post-doc at le Laboratoire d’imagerie, de vision et d’intelligence artificielle (LIVIA lab) at l’École de technologie supérieure (ÉTS) in collaboration with McGill university’s Rosalind & Morris Goodman Cancer Research Centre (GCRC). He completed my PhD in computer science at the Institut National des Sciences Appliquées de Rouen Normandie (INSA Rouen Normandie) in LITIS lab, Apprentissage (Learning) team During his PhD, he conducted research on the regularization of neural networks through representation learning with particular focus on learning scenarios where only few training samples are available.

Lectures:
- Autoencoders and Restricted Boltzman
- Machines Transfer learning with CNN
- Optimization for Deep Networks

Rémi Cadène

Rémi Cadène is now working on Self-Driving Vehicules with Andrej Karpathy at Tesla. Before that, I did some postdoctoral studies at Sorbonne and Brown University. His scientific interest lies in understanding the underlying mechanisms of intelligence. His research is currently focused on learning complex behaviors with neural networks. He is working on novel architectures, learning approaches, theoritical frameworks and explainability methods. He likes to contribute to open-source projects and to read about neuroscience.

Lectures:
- Reccurrent Neural Networks
- Visual Question Answering

Mélanie Ducoffe

Mélanie Ducoffe is a Researcher at Airbus. Mélanie graduated from Ecole Normale Supérieure de Cachan, France. She holds a Ph.D. in deep learning from I3S laboratory, CNRS. Her main interests are about deep learning and machine learning in general. Up to now, she has been working mostly in computer vision, 3d gestures recognition, and computational linguistics. She recently joined Airbus as a data scientist.

Lectures:
- Generative Adversarial Networks
- Optimization for Deep Networks
- Active learning for Deep Nets

Frederic Precioso

Since 2011, Frederic Precioso is Professor at Université Côte d'Azur, lecturer at the École d'ingénieur Polytech'Nice Sophia, member of the SPARKS (Scalable and Pervasive softwARe and Knowledge Systems) team of the I3S UMR 7271 CNRS-UNS laboratory. He is member of Maasai, a Joint Research Project between INRIA-CNRS-UCA. His main research interests are: Machine learning, Deep Learning, for many application domain. Since September 2018, he is Scientific and Program Officer for AI at the National Research Agency (ANR) for both State Investment Programmes Division and Digital Technology and Mathematics Dept.

Lectures:
- Deep Learning Bases
- Introduction to Convolutional Neural Networks
- Optimization for Deep Networks

Jakob Verbeek 

Since January 2020, he is a research scientist at Facebook AI Research in Paris. Before that, he was a senior researcher at Inria Grenoble working on machine learning and computer vision in the Thoth research team.

Lectures:
- Attention Model for Image Captioning
- Convolutional Neural Fabrics