I have been a CNRS Research Engineer since 2006. At present, I am coordinating the activities of CRISE / NCC (the computing facility of the INT, which includes the Neuro-Computing Center / NCC). I’m also a member of two research teams at INT : MECA and BANCO

My research focuses on developing and applying machine learning tools for new problems encountered in neuroscience. For this, I collaborate with the Qarma team of the Laboratoire d’Informatique Fondamentale de Marseille. At the moment, my main interest is to understand, model and exploit inter-individual differences measured through multi-modal MRI to better understand brain functions, using a generic framework called inter-subject learning.

Recent highlights :
 2017 : two papers that include new applications of inter-subject learning : the first one to demonstrate structure-function relationships (Anatomo-functional correspondence in the superior temporal sulcus) and the second one to quantify the power of EEG features in newborns to predict language acquisition (Enhanced Neonatal Brain Responses To Sung Streams Predict Vocabulary Outcomes By Age 18 Months)
 2017 : yet another demonstration of the usefuleness of our graph-kernel approach to design predictive models, this time for diffusion-MRI : Learning from Diffusion-Weighted Magnetic Resonance Images using graph kernels
 2016 : a new paper using our graph kernel has been accepted to Medical Image Analysis : Structural graph-based morphometry : A multiscale searchlight framework based on sulcal pits
 2015 : I have, finally, defended my PhD thesis in machine learning applied to neuroimaging : A multi-source perspective on inter-subject learning. Contributions to neuroimaging.
 2015 : our ANR project LIVES (Learning with Interacting ViEwS) has been funded ; I am the coordinator of the INT team and we will design and apply multi-modal machine learning methods on MRI data (anatomical, structural, resting-state, task-functional)
 2014 : our graph kernel paper has been accepted in Plos ONE : Graph-based inter-subject pattern analysis of fMRI data ; the source code and dataset are available here
 2013 : release of Vobi One, the first open source software suite dedicated to the processing of functional optical imaging ; the paper is available here
 2013 : co-PI of the PEPS BMI CAMPA (CAractérisation Multimodale des déficits sensori-moteurs Post-AVC) project ;
 2011 : organizer and chair of the MLNI workshop, which gathered leading researchers in machine learning and neuroimaging ;
 2010-2012 : PI of the Neuro-IC GRABBR (GRAph-Based Brain Reading) project ;
 2009 : publication of our PNAS paper on ICA and fMRI, which includes some the work I did during my six years at Princeton University.