I am a post-doctoral research at École Normale Supérieure, Paris, in the laboratory of Gabriel Peyré. I hold a Ph.D. in machine learning, that I prepared in Inria Parietal, from September 2015 to September 2018.
I am interested in optimization methods, and especially matrix factorization techniques, for very large datasets such as those produced by functional Magnetic Reasonance Imaging (fMRI). I developed new models for multi-study brain decoding, and new tools for representation learning in natural language processing.
My Ph.D. was obtained under the supervision of Gaël Varoquaux, Julien Mairal and Bertrand Thirion. I obtained a graduate degree at École Polytechnique, and a Master of Science in applied mathematics and machine learning at Télécom ParisTech and École Normale Supérieure de Cachan, in France.
My detailed resume can be found here. More details on the research and software that I do.
- 28/01/19 Slides for an extended presentation of Differentiable Dynamic Programming for Stuctured Prediction and Attention Paper
- 11/01/18 Started working as a post-doct with Gabriel Peyré, in ENS, Paris
- 10/25/18 Preprint of our work Extracting Universal Representations of Cognition across Brain-Imaging Studies on multi-dataset decoding for functional MRI data
- 09/28/18 Defended my PhD thesis (Slides, Thesis) at NeuroSpin.
- 05/09/18 Our paper Differentiable Dynamic Programming for Stuctured Prediction and Attention was accepted at ICML 2018. Paper. Presented on the 07/12/18 at Stockholm Slides
- 02/11/17 Our NIPS 2017 paper Learning Neural Representations of Human Cognition across Many fMRI Studies is available.
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