About

Currently professor at CNAM and the CEDRIC laboratory.

Doing research about statistics and optimization methods for various applications in machine learning and signal processing:

• Dimension reduction and variable selection: probabilistic/sparse PCA, graphical models, robust subspace recovery, low-rank matrix factorization.

• Information geometry: performance bounds, Riemannian optimization, and classification/clustering with metrics induced by statistical models.

• Statistical signal processing: robust signal subspace and structured covariance matrix estimation, adaptive detection/beamforming.