Nicolas Boumal

Nicolas Boumal is an Associate Professor in the Department of Mathematics at École Polytechnique Fédérale de Lausanne. His research focuses on continuous optimization, with an emphasis on theoretical and algorithmic developments. He teaches courses such as Continuous Optimization, Linear Algebra, and Topics in Continuous Optimization. His work includes both foundational theory and practical applications, with a focus on improving technical communication skills among students. He is affiliated with the Optimization Laboratory at EPFL and maintains an active research profile.

Nicolas Boumal is a researcher at Ecole Polytechnique Fédérale de Lausanne (EPFL) specializing in continuous optimization, statistical estimation, numerical analysis, nonconvex optimization, and geometric optimization. His work focuses on developing and analyzing algorithms for optimization problems on manifolds, with applications in signal processing, machine learning, and data science. He has contributed to the development of tools like Manopt and has published extensively on topics such as Riemannian trust-region methods, low-rank matrix completion, and nonconvex phase retrieval. His research emphasizes the theoretical and practical aspects of optimization on smooth manifolds, including convergence guarantees and algorithmic efficiency.