Currently associate professor at University Paris Nanterre and the LEME 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, 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.