I am currently a Postdoctoral research associate at Computer Science and Artificial Intelligence Laboratory (CSAIL), MIT and Qatar Computing Research Institute (QCRI), HBKU.
I am working with Professor Antonio Torralba, Dr. Ferda Ofli and Dr. Ingmar Weber.
My research lies at the intersection of computer vision, machine learning and multimedia modeling.
Specifically, I am interested in building food recognition systems and applying them on social media data in order to understand health habits.
Previously (in June 2018), I obtained a PhD in Computer-Vision and Machine-Learning at CentraleSupélec and Alternative Energies & Atomic Energy Commission (CEA), under the supervision of Dr. Hervé Le Borgne (CEA) and Professor Céline Hudelot (Centrale-Supélec).
My research centers around Deep-Learning and its applications to Computer-Vision, in particular object/scene recognition, content-based image retrieval and video recognition. More specifically, I am interested in the learning of image representations using Deep Convolutional Neural Networks (DCNNs) in order to re-use them (through a transfer-learning scheme) when facing with small datasets that contains too few images and/or classes to learn representations from scratch. The learning of these image-representations is based on the unsupervised generative aspect of DCNNs which is quite powerful but complex, making it hard to understand and thus very hard to control as we want. Keywords: Computer-Vision, Machine-Learning, Deep-Learning, Image Understanding, Object/Scene Recognition.
- Julien Girard, (will start a PhD at CEA LIST) - Inès Chami, (will start a PhD at Stanford University)
Artificial Intelligence tutorials for Master of Science (M.Sc) students. Rational, Expert and Logical agents, Machine Learning, Basics of NLP, Basics of Computer-Vision, etc. Framework: Keras. [Python]Centrale-Supélec - 2017
Deep Learning tutorials for Master of Science (M.Sc) students. Linear Regression, Multi-Layer Perceptron (MLP), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Transfer-Learning, Fine-Tuning, etc. Framework: TensorFlow. [Python]Centrale-Supélec - 2017
Human-Computer Interaction for 1st year IUT students.IUT d'Orsay (University of Paris-Sud) - 2017
Asian Conference on Computer Vision 2018: Two papers.
IEEE Computer Vision and Pattern Recognition 2018: Seven papers.
International Conference on Learning Representations 2018: Two papers.
Advances in Neural Information Processing Systems 2017: Two papers.
A website dedicated to novice students (of Centrale-Supelec) in the field of Artificial Intelligence (AI), that lists many useful links, including theoretical and practical courses, frameworks, databases and misc tools.Project for Centrale-Supélec Link to AI4DTY website
Development of a module of a driving assistance application. The module consisted to detect pedestrians on video-frames obtained from an embedded camera. I developed it using OpenCV and LibSVM libraries. [C++]Scholar Project
Development of a module of a driving assistance application. The module consisted to detect and recognize road signs on video-frames obtained from an embedded camera. I developed it using OpenCV and LibSVM libraries. [C++]Scholar Project
Development of a hand-written digit recognition system using a shallow neural network that contains multiple hidden-layers. I developed it from scratch, i.e, without any library or framework. [Matlab]Scholar Project