Lars Grasedyck

Lars Grasedyck is a Professor of Numerical Analysis at RWTH Aachen University. His research focuses on hierarchical matrices, tensor approximation, and numerical methods for partial differential equations and matrix equations. He has contributed to applications in biomedical engineering, particularly EEG/MEG inverse problems, and is involved in software development (HLIB, HLIB-pro).

• Education: Diploma and Ph.D. in Mathematics at Christian-Albrechts-Universität zu Kiel (1998, 2001), Postdoctoral work at Max Planck Institute, Leipzig (2002-2010).
• Research: Specializes in high-dimensional numerical methods, low-rank matrices, and tensors with applications in PDEs, uncertainty quantification, and biomedical modeling.
• Projects: Leads DFG-funded initiatives on adaptive tensor networks for parametric PDEs and tumor progression modeling.
• Advising: Supervises doctoral students including Thong Le, Maren Klever, and Dieter Moser.
• Software: Developed HLib and HLib-pro for hierarchical matrix computations.
• Conferences: Active in GAMM Fachausschuss Numerische Analysis, organizing workshops and symposia globally.