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Martin Siebenborn

msiebenborn
Junior Professor für Optimierung und Approxmiation

Fachbereich Mathematik
Bundesstraße 55 (Geomatikum)
Raum 105
20146 Hamburg

Tel.: +49 40 42838-5156
Fax.: +49 40 42838-5117
E-Mail: martin.siebenbornREMOVE@uni-hamburgREMOVE.de

pgp: 0xa3c70dfd

Lehre · Publikationen · CV

Forschungsschwerpunkte

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  • Shape optimization and interface identification
  • High performance optimization algorithms
  • Algorithmic scalability for PDE constrained optimization
Example: Minimizing energy dissipation in a Stokes flow in mesh-quality preserving shape spaces

Sprechstunden

Im Semester:Di 14-16
Vorlesungsfreie Zeit:Nach Vereinbarung

Lehre

WiSe 19/20Vorlesung: Numerische Mathematik, Geom H1, Mo 10-12, Do 14-16
SoSe 19Vorlesung: Numerical Methods for PDEs (englisch), Geom H5, Di 12-14, Fr 8-10
WiSe 18/19Vorlesung: Optimization of Complex Systems (englisch), Geom H6, Mi 12-14, Fr 8-10
Übung: Optimization of Complex Systems (englisch), Geom 142, Fr 10-12
SoSe 18Vorlesung: Algorithms and Data Structure (englisch), Geom H5, Di 12-14
Vorlesung: Optimization (englisch), Geom H5, Do 10-12

Publikationen

Journal articles:

  • M. Siebenborn and A. Vogel. A shape optimization algorithm for cellular composites. Submitted to Springer Computing and Visualization in Science (2019), arxiv.org/1904.03860.
  • M. Siebenborn and J. Wagner. A Multigrid Preconditioner for Tensor Product Spline Smoothing. Submitted to Springer Journal of Scientific Computing (2019), arxiv:1901.00654.
  • T. Etling, R. Herzog, and M. Siebenborn. Optimum Experimental Design for Interface Identification Problems. Submitted to SIAM Journal on Scientific Computing (2019), arXiv:1808.05776.
  • M. Siebenborn. A shape optimization algorithm for interface identification allowing topological changes. In: Journal of Optimization Theory and Applications 177(2) (2018), 306-328.
  • M. Siebenborn and K. Welker. Algorithmic Aspects of Multigrid Methods for Optimization in Shape Spaces. In: SIAM Journal on Scientific Computing 39.6 (2017), B1156-B1177.
  • V. Schulz, M. Siebenborn, and K. Welker. Efficient PDE constrained shape optimization based on Steklov-Poincaré-Type metrics. In: SIAM Journal on Optimization 26.4 (2016), pp. 2800-2819.
  • L. Grasedyck, C. Löbbert, G. Wittum, A. Nägel, V. Schulz, M. Siebenborn, R. Krause, P. Benedusi, U. Küster, and B. Dick. Space and Time Parallel Multigrid for Optimization and Uncertainty Quantification in PDE Simulations. In: Software for Exascale Computing - SPPEXA 2013-2015. Ed. by H.-J. Bungartz, P. Neumann, and E. W. Nagel. Springer International Publishing, (2016), pp. 507-523.
  • V. Schulz and M. Siebenborn. Computational comparison of surface metrics for PDE constrained shape optimization. In: Computational Methods in Applied Mathematics 16.3 (2016), pp. 485-496.
  • A. Nägel, V. Schulz, M. Siebenborn, and G. Wittum. Scalable shape optimization methods for structured inverse modeling in 3D diffusive processes. In: Computing and Visualization in Science 17.2 (2015), pp. 79-88.
  • V. Schulz, M. Siebenborn, and K. Welker. Structured Inverse Modeling in Parabolic Diffusion Problems. In: SIAM Journal on Control and Optimization 53.6 (2015), pp. 3319-3338.
  • M. Siebenborn, V. Schulz, and S. Schmidt. A curved-element unstructured discontinuous Galerkin method on GPUs for the Euler equations. In: Computing and Visualization in Science 15.2 (2012), pp. 61-73.

Refereed proceedings:

  • V. Schulz, M. Siebenborn, and K. Welker. PDE constrained shape optimization as optimization on shape manifolds. In: Geometric Science of Information. Ed. by F. Nielsen and F. Barbaresco. Vol. 9389. Lecture Notes in Computer Science. 2015.
  • V. Schulz, M. Siebenborn, and K. Welker. Towards a Lagrange-Newton approach for PDE constrained shape optimization. In: New trends in shape optimization. International Series of Numerical Mathematics. Springer, 2015.
  • M. Siebenborn and V. Schulz. GPU Accelerated Discontinuous Galerkin Methods for Euler Equations and Its Adjoint. In: Proceedings of the High Performance Computing Symposium HPC 13. San Diego, California: Society for Computer Simulation International, 2013, 3:1-3:7.

Other publications:

  • M. Siebenborn. Discontinuous Galerkin approaches for HPC flow simulations on stream processors. PhD thesis. Trier University, Germany, 2014.

Software:


CV

Seit 02/2018Junior Professor (W1), Fachbereich Mathematik, Universität Hamburg
01/2014 - 01/2018Postdoc im DFG-SPP "Software for Exascale Computing" (SPPEXA), Universität Trier
01/2014Promotion in Mathematik, Universität Trier, bei V. Schulz
11/2010 - 01/2014Wissenschaftlicher Mitarbeiter, Fachbereich Mathematik, Universität Trier
10/2010Diplom in Mathematik, Universität Trier
04/2006 - 10/2010Studium der Mathematik mit Nebenfach Informatik, Universität Trier

  Seitenanfang  Impressum 2019-07-03, Martin Siebenborn