Laurent El Ghaoui

Laurent El Ghaoui is a Professor Emeritus in the Department of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley. His research focuses on Control, Intelligent Systems, and Robotics (CIR), with specific interests in robust and convex optimization, decision-making under uncertainty, and statistical estimation. He joined UC Berkeley in 1999 as an Acting Associate Professor and was granted tenure in 2001. Prior to his academic career, he was a faculty member at the Ecole Nationale Supérieure de Techniques Avancées in France and held part-time teaching appointments at other institutions. His work has been published in numerous conferences and journals, and he has contributed to various research centers at UC Berkeley.

Laurent El Ghaoui is a researcher specializing in Convex, Robust, and Sparse Optimization with applications in Machine Learning. His work focuses on developing robust optimization techniques for uncertain data and improving the reliability of machine learning models. He has contributed to areas such as linear matrix inequalities, semidefinite programming, and conic programming. His research includes robust solutions for least-squares problems, portfolio optimization, and classification methods. El Ghaoui's publications address challenges in system and control theory, wireless sensor networks, and sparse covariance selection, emphasizing theoretical principles and practical applications in optimization and machine learning.