Jérôme-Alexis Chevalier
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Post-doc in Machine Learning |
About me
I am currently a post-doc in Machine Learning at Inria Saclay Île-de-France. Following my PhD. research, I am lucky to work under the supervision of Bertrand Thirion and Joseph Salmon.
My research focus on handling uncertainty in the challenging context of high dimensional regression problem. The primary field of application is neuro-imaging.
During my PhD., I had the chance to be a member of the parietal team of the Inria Saclay-Île-de-France Research Centre.
I am thankfull to the NeuroSpin Research Center and to Telecom Paris for hosting me during the thesis, allowing a better collaboration with my supervisors.
I am also thankfull to the Labex Digicosme and to the Université Paris-Saclay who funded my thesis.
Before my PhD., I graduated from Université Paris-Diderot and ENSEIRB-MATMECA.
More information about my background can be found on my resume.
Research Interests
Though I am interested in Machine Learning and Statistics in general, my main interests are statistical methods in high dimension, clustering methods and ensembling methods.
I also enjoy to code in Python on open source projects: I am one of the lead developers of HiDimStat that provides high-dimensional statistical inference tools and a contributor of Nilearn which is a reference package for the analysis of fMRI data.
To benefit from feedbacks from the Machine Learning and neuro-scientific community, I have published several papers in conferences and journals, my publications are all available here.