Mission

Research Interests: Multiple comparison procedures, Multivariate Analysis, Brain connectivity, Modern graph theory, Statistical Classification, diffusion MRI image analysis, Time series, Bayesian smoothing.

Current work

My current interest is the statistical brain connectivity analysis, especially, the voxel-based, node-based or connection based analysis. Such analysis involves the problem of multiple comparisons or multiple testing. The work covers three aspects.
1. The general problem of multiple comparison procedures. The objective is to find a multiple comparison procedure that is optimal under an optimality criterion. The criterion makes the compromise between the false and the true discoveries via a weighted classification. We are now focusing on the best choice of multiple comparison procedure in the family of the scaled MCPs.
2. The multiple comparison procedures under dependence. In many fields of application and particularly, in the field of neuro-imaging, the observation are structured into dependent components. The aim is to use this information to increase the power of detection of real effects. We develop methods that need as much as possible of assumptions, so they can be applied in for large variety of problems.
3. The applicability of the theoretical methods in the brain connectivity context.
The brain connectivity can be represented by networks (weighted graphs). All network topology measures are investigated for adapted use in the context. In addition, new clinical results are obtained by applying the developed methods.

Biography

PhD. Applied mathematics and Electrical engineering, EPFL, 2013.
Diploma, Applied Mathematics, EPFL, 2009.