Mohammed Nabil EL KORSO

Mohammed Nabil EL KORSO is a Professor at CentraleSupélec, part of the University of Paris-Saclay. He is affiliated with the Laboratoire des Signaux et Systèmes (L2S). His research focuses on statistical signal processing, machine learning, detection/estimation theory, and robust signal processing, with applications in radioastronomy, radar systems, and source localization. He has contributed extensively to methodologies like Kalman filtering, covariance estimation, and array processing.

His work emphasizes robust techniques for handling non-Gaussian noise and interference, particularly in radio interferometry and SAR imaging. Key contributions include algorithms for array calibration, RFI mitigation, and subspace estimation. His research also addresses challenges in distributed and adaptive signal processing, with applications to vital signs monitoring and robotic systems.

He has published over 50 journal articles and conference papers, focusing on performance bounds (Cramér-Rao, Weiss-Weinstein), Bayesian methods, and practical implementations for large-scale systems. His recent work includes advancements in low-cost interferometric imaging and phase estimation for SAR time series.

EL KORSO collaborates with international projects like the Square Kilometre Array (SKA), contributing to technological developments in radio astronomy. He supervises research in signal processing labs and actively participates in academic conferences such as EUSIPCO and ICASSP.