Machine Learning, Neuroimaging, Scientific computing, Software Engineering, Bioinformatics, High Dimensional Data. Machine Learning in Neuroimaging
I am a research scientist at NeuroSpin/CEA, Paris-Saclay (map): a MRI neuroimaging center within the CEA (Commissariat à l’énergie atomique, Saclay, France). I am developing machine learning algorithms (classification/regression) and multivariate/univariate statistics analysis tools. Those algorithms aim to provide computer-aided diagnosis/prognosis tools or biomarkers discovering methods for brain diseases. I am now integrating genetic (DNA array) together with neuroimaging. The specificity of such data is their large dimension which requires new specific feature extraction/selection and sparse and structured machine learning (convex optimisation) algorithms.
I am a core contributor of ParsimonY a Machine Learning library in Python dedicated to high dimensionnal structured input data such as brain images (MRI, PET) or genetics data (DNA, RNA).
(Former) Students in (Co-)Supervision
- Pietro Gori (Post-doc, 2016-now) together with JF Mangin and J Houenou
- Amicie de Pierrefeu (PhD, 2016-now) together with Philippe Ciuciu
- Fouad Hadj Selem (Post-doc, 2013-2015) together with V Frouin and JF Mangin
- Tommy Lofstedt (Post-doc, 2013-2015) together with V Frouin
- Mathieu Dubois (Post-doc, 2013-2014) together with V Frouin
- Clémence Pinaud (Engineer trainee 2014)
- Jinpeng Li (Research Engineer 2013-2014)
- Cecilia Damon (PhD defended on 2011) together with JB Poline
- Edith Lefloch (PhD defended on 2012) together with V Frouin