Generate a tailored SOP for Dr. Bart Vandereycken. Improve your application with a focused, well-structured draft.
Bart Vandereycken is an associate professor in the numerical analysis group at the University of Geneva. He specializes in the research of large-scale high-dimensional problems, particularly those solved numerically with low-rank matrix tensor techniques. His notable work addresses significant challenges such as the electronic Schrödinger equation, parametric partial differential equations, and low-rank matrix completion. With a profound focus on practical algorithms, he employs Riemannian matrix manifolds and employs techniques from numerical linear algebra and optimization. Bart's research interests encompass nonlinear eigenvalue problems, machine learning, and multilevel preconditioning. He has served as an associate editor for the SIAM Journal on Matrix Analysis and Applications, as well as for Linear Algebra and its Applications. Prior to his current position, he was an instructor in mathematics at Princeton University from September 2012 to January 2015, and he completed a postdoctoral fellowship at EPF Lausanne and ETH Zurich. He obtained his PhD from KU Leuven in December 2010.
University of Geneva • Geneva, Switzerland
Associate professor in the numerical analysis group.
Princeton University • Princeton, NJ
Instructor of mathematics.
EPF Lausanne and ETH Zurich •
Postdoctoral research position.
Includes Department of Management, Finance, Economics, and Statistics programs. GMAT is strongly encouraged but not mandatory for most GSEM masters.