- Assistant professor at Ecole Centrale Marseille and research at team QARMA in LIS laboratory.
- Teaching Computer Science, Data Science, Machine Learning, and Computer Vision courses at ECM.
- Working on Machine Learning and Computer Vision
December 2021: 2 master internships opening on interpretability of Convolutional Neural Networks as part of the UnLIR project: Learning a decoder to produce interpretable saliency maps – saliency segmentation for CNN interpretability evaluation– Contact: email@example.com
July 2021: Hanwei Zhang joins our group as post doctoral researcher.
November 2020: Felipe Torres joins our group as PhD.
July 2020: Open PhD position (multiple opening) as part of the UnLIR project: Learning discriminative representations to interpret image recognition models – Computer vision and deep learning. Position closes on August 16th – PhD starting in September / October – Contact: firstname.lastname@example.org
December 2019: Open Master internship: Unsupervised learning for image recognition – Computer vision and deep learning
October 2019: The ANR JCJC project UnLIR is accepted (internships, one PhD, and one postdoc available).
I received a Master degree in Intelligent Systems from the University of Toulouse, France, in 2007. During my master I studied at the University of Plymouth, England, at the University of Calgary, Canada, and at the Technical University of Berlin, Germany. From 2008 to 2011, I worked toward the Ph.D. degree in the LaBRI at the University of Bordeaux in collaboration with MIRANE S.A.S. Then, I obtained a Lecturer / Researcher (ATER) position in Bordeaux: I taught at the ENSEIRB-MATMECA and worked as a researcher at the LaBRI. I then worked as a postdoc at the University of Amsterdam (UVA) at the Intelligent System Lab (ISLA), at the University of Caen, in the image team of the GREYC lab, and at INRIA Rennes in the Linkmedia Team. I’m now Assistant professor at Ecole Centrale Marseille and belong to the QARMA team at LIS
- Deep learning
- Part-based image recognition
- (Fine-grained) image classification
- Image retrieval
- Interpretability of models
- Image denoising