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Bart Vandereycken is an Associate Professor at the University of Geneva in the Section of Mathematics. He specializes in numerical analysis, focusing on large-scale high-dimensional problems solved using low-rank matrix tensor techniques. His research covers applications such as the electronic Schrödinger equation and parametric partial differential equations, as well as low-rank matrix completion. Prior to his position at the University of Geneva, he served as an Instructor in Mathematics at Princeton University from September 2012 to January 2015 and completed a postdoctoral fellowship at EPF Lausanne and ETH Zurich. Vandereycken obtained his PhD from KU Leuven in December 2010. His current research interests include nonlinear eigenvalue problems, machine learning, and multilevel preconditioning. He also emphasizes the development of practical algorithms formulated in Riemannian matrix manifolds, employing techniques from numerical linear algebra and numerical optimization.
Princeton University • Princeton, NJ
Instructed courses in Mathematics.
EPF Lausanne and ETH Zurich • Lausanne and Zurich, Switzerland
Conducted research in numerical analysis and algorithms.
Includes Department of Management, Finance, Economics, and Statistics programs. GMAT is strongly encouraged but not mandatory for most GSEM masters.