Dr. A. (Alexander) Heinlein
Dr. A. (Alexander) Heinlein
Profile
Expertise
Alexander Heinlein is assistant professor in the Numerical Analysis group of the Delft Institute of Applied Mathematics (DIAM), Faculty of Electrical Engineering, Mathematics & Computer Science (EEMCS), at the Delft University of Technology (TU Delft).
His main research areas are numerical methods for partial differential equations and scientific computing, in particular, solvers and discretizations based on domain decomposition and multiscale approaches. He is interested in high-performance computing (HPC) and solving challenging problems involving, e.g., complex geometries, highly heterogenous coefficient functions, or the coupling of multiple physics. More recently, Alexander also started focusing on the combination of scientific computing and machine learning, a new research area also known as scientific machine learning (SciML). Generally, his work includes the development of new methods and their theoretical foundation as well as their implementation on current computer architectures (CPUs, GPUs) and application to real world problems.
Expertise
Publications
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2023
A Multilevel Extension of the GDSW Overlapping Schwarz Preconditioner in Two Dimensions
Alexander Heinlein / Oliver Rheinbach / Friederike Röver
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2023
An Experimental Study of Two-level Schwarz Domain-Decomposition Preconditioners on GPUs
Ichitaro Yamazaki / Alexander Heinlein / Sivasankaran Rajamanickam
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2023
Comparison of arterial wall models in fluid–structure interaction simulations
D. Balzani / A. Heinlein / A. Klawonn / O. Rheinbach / J. Schröder
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2023
Machine learning for phase-resolved reconstruction of nonlinear ocean wave surface elevations from sparse remote sensing data
Svenja Ehlers / Marco Klein / Alexander Heinlein / Mathies Wedler / Nicolas Desmars / Norbert Hoffmann / Merten Stender
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2023
Reduced order fluid modeling with generative adversarial networks
Maarten Kemna / A. Heinlein / Cornelis Vuik
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