Michael Schlottke-Lakemper

I am an interim professor (Vertretungsprofessor) for Computational Mathematics and research software engineer at the Applied and Computational Mathematics Research Lab at RWTH Aachen University, Germany. For this position, I am currently on leave from heading the Training & Scalable Algorithms group at the High-Performance Computing Center Stuttgart (HLRS). My research focus is on numerical methods for adaptive multi-physics simulations, research software engineering for high-performance computing, and scientific machine learning.

Interests

Education

Dr.-Ing. in Computational Engineering Science, 2017

RWTH Aachen University, Germany
Dipl.-Ing. in Aerospace Engineering, 2011

University of Stuttgart, Germany
MS in Aerospace Engineering, 2010

Georgia Institute of Technology, US

Recent Publications

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Hendrik Ranocha, Michael Schlottke-Lakemper, Jesse Chan, Andrés M. Rueda-Ramírez, Andrew R. Winters, Florian Hindenlang, Gregor J. Gassner

Hendrik Ranocha, Andrew R. Winters, Hugo Guillermo Castro, Lisandro Dalcin, Michael Schlottke-Lakemper, Gregor J. Gassner, Matteo Parsani

Hendrik Ranocha, Michael Schlottke-Lakemper, Andrew R. Winters, Erik Faulhaber, Jesse Chan, Gregor J. Gassner

Michael Schlottke-Lakemper, Andrew R Winters, Hendrik Ranocha, Gregor J Gassner

Hendrik Ranocha, Michael Schlottke-Lakemper, Andrew Ross Winters, Erik Faulhaber, Jesse Chan, Gregor Gassner

Courses and supervised students

Winter 2022/2023, website

Summer 2021, website

Winter 2020/2021, website

Summer 2020, website

Winter 2019/2020, website

N. Neher, Particle-based parallel multiphysics simulations (tbd.) (expected 2027)

H. Zunker, Robust and self-learning shock capturing with artificial neural networks (2022)
D. Sklema, Perturbation kinetic equations for turbulence simulations (2022)
E. Faulhaber, Octree-Based AMR on Cubed Sphere Grids with Discontinuous Galerkin Methods (2022)
K. Scislak, Deep learning-based boundary conditions for computational aeroacoustics (2021)
J. Odenthal, Shock capturing with articial neural networks (2021)
M. Matysiak, Turbulence modeling with artificial neural networks for the viscous Burgers’ equation (2020)
J. Vorspohl, A comparison between SBP-SAT and DG operators for computational aeroacoustics on non-conforming meshes (2019)
B. Peeters, Combustion noise prediction with the direct-hybrid method for computational aeroa- coustics (2017)
A. Niemöller, Dynamic load balancing for direct-hybrid computational aeroacoustics, 2017
A. Mengel, Investigation of the sound generated by the flow behind a rectangular cylinder with the direct-hybrid method for computational aeroacoustics (2016)
J. Miller, Software Cost Estimation for the Development Effort applied to Multi-node GPU Aeroa- coustics Simulations (2016)
L. Liberson, Implementation and validation of boundary conditions for a discontinuous Galerkin- based solver for the acoustic perturbation equations (2014)
S. Berger, Implementation and validation of an adaptive hp-refinement method for the discontinuous Galerkin spectral element method (2014)

L. Christmann, Non-reflecting boundary conditions for computational aeroacoustics based on arti- cifial neural networks (2022)
L. Hristozova, Comparison of the discontinuous Galerkin method with SBP-SAT finite difference operators for aeroacoustics problems (2018)
P. Antony, Development of a coupled discontinuous Galerkin–finite volume scheme, 2018
F. Zechel, Dissipations- und Dispersionseigenschaften der unstetigen Galerkin Spektrale Elemente Methode (2016)
A. Niemöller, Comparison of different methods for solving the acoustic perturbation equations (2015)
M. Nicolini, Software Cost Estimation of GPU-accelerated Aeroacoustic Simulations with OpenACC (2015)
J. Stratmann, Simulating advection-diffusion problems with the discontinuous Galerkin method (2015)
A. Marwege, Conservative interpolation methods for nodal discontinuous Galerkin schemes (2015)

Last updated on Dec 23, 2021