Fachbereich Mathematik 
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Martin Siebenborn

msiebenborn
Junior Professor for Optimization and Approximation

Department of Mathematics
Bundesstraße 55 (Geomatikum)
Room 105
20146 Hamburg

phone: +49 40 42838-5156
telefax: +49 40 42838-5117
email: martin.siebenborn (at) uni-hamburg.de

pgp: 0xa3c70dfd

Teaching · Publications · Short CV

News:

Applicants for one PhD position in the group "Optimization and Approximation" starting on October 1, 2019, are welcome.


Research focus:

logo
  • 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

Office hours:

During term:Tue 2-4 p.m.
During term break:by appointment

Teaching

Summer term 19Lecture: Numerical Methods for PDEs, Geom H5, Tue 12-2 p.m., Fr 8-10 a.m.
Winter term 18/19Lecture: Optimization of Complex Systems, Geom H6, We 12-2 p.m., Fr 8-10 a.m.
Tutorial: Optimization of Complex Systems, Geom 142, Fr 10-12 a.m.
Summer term 18Lecture: Algorithms and Data Structure, Geom H5, Tue 12-2 p.m.
Lecture: Optimization, Geom H5, Thu 10-12 a.m.

Publications

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:


Short CV

Since 02/2018Junior Professor (W1), Department of Mathematics, Universität Hamburg
01/2014 - 01/2018Postdoc in DFG priority program "Software for Exascale Computing" (SPPEXA), Univeristät Trier
01/2014Doctor in Mathematics, Universität Trier, with V. Schulz
11/2010 - 01/2014Research Assistant, Department of Mathematics, Universität Trier
10/2010Diploma in Mathematics, Universität Trier
04/2006 - 10/2010Studies of Mathematics with minor Computer Science, Universität Trier

  Seitenanfang  Impress 2019-06-25, Martin Siebenborn