Department of Mathematics
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Junior Professor for Optimization and Approximation
Department of Mathematics
Bundesstraße 55 (Geomatikum)
Room 105
20146 Hamburg
phone: +49 40 42838-5156
email: martin.siebenborn @uni-hamburg .de
Webpage: https://www.math.uni-hamburg.de/personen/siebenborn/
(this way to the possibly more complete Homepage in the old layout)
Martin Siebenborn
Department of Mathematics
Bundesstraße 55 (Geomatikum)
Room 105
20146 Hamburg
phone: +49 40 42838-5156
email: martin.siebenborn @uni-hamburg .de
Webpage: https://www.math.uni-hamburg.de/personen/siebenborn/
Projects · Teaching · Publications · Short CV
Team
Projekte
- 04/2022 - 03/2023, HLRN Project,
An optimal shape matters - Developing Scalable Shape Optimization Algorithms for Fluid Dynamics and Structural Mechanics
, Link - 04/2020 - 10/2023, Landesforschungsförderung LFF-GK11,
Simulation-Based Optimal Design of Dynamic Systems under Uncertainties
, Link - 04/2020 - 10/2024, DFG Research Training Group 2583,
Modelling, Simulation and Optimization of Fluid Dynamics Applications
, Link - 04/2016 - 10/2020, DFG Research Training Group 2126,
Algorithmic Optimization
, Link
Research focus
- Shape optimization and interface identification
- High performance optimization algorithms
- Algorithmic scalability for PDE constrained optimization
Example: Minimizing energy dissipation in a Navier-Stokes flow in shape spaces suitable for scalable multigrid algorithms
Example: Reference surface mesh and optimized geometry in stationary Navier Stokes flow
Teaching
Summer term 22 | Lecture: Scientific Computing, Geom HS4, Thu 4-6 p.m. |
Tutorial: Scientific Computing, Sed 19 Room 208, Thu 2-4 p.m. | |
Seminar: Numerische Algorithmen in C++ | |
Winter term 21/22 | Lecture: Optimization of Complex Systems, online, We 2-4 p.m., Thu 12-2 p.m. |
Tutorial: Optimization of Complex Systems, online, Mo 2-4 p.m. | |
Summer term 21 | Lecture: Optimization, online, We 4-6 p.m. |
Lecture: Numerical Methods for PDEs, online, Tue 12-2 p.m., Fr 8-10 a.m. | |
Tutorial: Numerical Methods for PDEs, online, Mo 2-4 p.m. | |
Winter term 20/21 | Lecture: Optimization of Complex Systems, online, We 2-4 p.m., Thu 12-2 p.m. |
Summer term 20 | Seminar: Numerische Algorithmen in C++ |
Winter term 19/20 | Lecture: Numerische Mathematik, Geom H1, Mo 10-12 a.m., Thu 2-4 p.m. |
Lecture: Optimierung für Studierende der Informatik, Geom H1, Tue 4-6 p.m. | |
Summer term 19 | Lecture: Numerical Methods for PDEs, Geom H5, Tue 12-2 p.m., Fr 8-10 a.m. |
Winter term 18/19 | Lecture: 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 18 | Lecture: Algorithms and Data Structure, Geom H5, Tue 12-2 p.m. |
Lecture: Optimization, Geom H5, Thu 10-12 a.m. |
Office hours
During term: | Tue 2-4 p.m. |
During term break: | by appointment |
Publications
Submitted preprints:
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J. Pinzon, M. Siebenborn, and A. Vogel.
Scalable Multigrid Algorithms for Fluid Dynamic Shape Optimization
. Accepted for publication: Proceedings of the High Performance Computing in Science & Engineering - 24rd Results and Review Workshop (2021). -
P.M. Müller, J. Pinzon, T. Rung, M. Siebenborn.
A Scalable Algorithm for Shape Optimization with Geometric Constraints in Banach Spaces
. Submitted to: SIAM Journal on Scientific Computing (2022), arxiv:2205.01912.
Journal articles:
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J. Pinzon and M. Siebenborn.
Fluid dynamic shape optimization using self-adapting nonlinear extension operators with multigrid preconditioners
. In: Optimization and Engineering (2022), 10.1007/s11081-022-09721-8. -
P. M. Müller, N. Kühl, M. Siebenborn, K. Deckelnick, M. Hinze, and T. Rung.
A Novel p-Harmonic Descent Approach Applied to Fluid Dynamic Shape Optimization
. Journal on Structural and Multidisciplinary Optimization (2021), 10.1007/s00158-021-03030-x. -
N. Kühl, J. Kröger, M. Siebenborn, M. Hinze, and T. Rung.
Adjoint Complement to the Volume-of-Fluid Method for Immiscible Flows
. Journal of Computational Physics (2021), 10.1016/j.jcp.2021.110411. -
M. Siebenborn and J. Wagner.
A multigrid preconditioner for tensor product spline smoothing
. In: Computational Statistics 36.4 (2021), pp. 2379–2411, 10.1007/s00180-021-01104-4. -
S. Onyshkevych and M. Siebenborn.
Mesh quality preserving shape optimization using nonlinear extension operators
. In: Journal of Optimization Theory and Applications 189.1 (2021), pp. 291–316, 10.1007/s10957-021-01837-8. -
J. Haubner, M. Siebenborn, and M. Ulbrich.
A Continuous Perspective on Shape Optimization Via Domain Transformations
. In: SIAM Journal on Scientific Computing 43.3 (2021), A1997-A2018, 10.1137/20m1332050. -
M. Siebenborn and A. Vogel.
A shape optimization algorithm for cellular composites
. In: PINT Computing and Visualization in Science (2021), 10.51375/IJCVSE.2021.1.5. -
J. Pinzon, M. Siebenborn, and A. Vogel.
Parallel 3d shape optimization for cellular composites on large distributed-memory clusters
. In: Journal of Advanced Simulation in Science and Engineering 7.1 (2020), pp. 117–135, 10.15748/jasse.7.117. -
T. Etling, R. Herzog, and M. Siebenborn.
Optimum Experimental Design for Interface Identification Problems
. In: SIAM Journal on Scientific Computing 41.6 (2019), 10.1137/18M1208125. -
M. Siebenborn.
A shape optimization algorithm for interface identification allowing topological changes
. In: Journal of Optimization Theory and Applications 177(2) (2018), 306-328, 10.1007/s10957-018-1279-4. -
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, 10.1137/16m1104561. -
V. Schulz, M. Siebenborn, and K. Welker.
Efficient PDE constrained shape optimization based on Steklov-Poincare-Type metrics
. In: SIAM Journal on Optimization 26.4 (2016), pp. 2800-2819, 10.1137/15M1029369. -
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, 10.1007/978-3-319-40528-5_23. -
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, 10.1515/cmam-2016-0009. -
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, 10.1007/s00791-015-0248-9. -
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, 10.1137/140985883. -
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, 10.1007/s00791-013-0197-0.
Refereed proceedings:
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J. Pinzon, M. Siebenborn, and A. Vogel.
High-Performance Shape Optimization for Linear Elastic Models of Epidermal Cell Structures
. In: High Performance Computing in Science and Engineering '20. Ed. by W. E. Nagel, D. H. Kröner, and M. M. Resch. Springer International Publishing, 2021, pp. 579–594. 10.1007/978-3-030-80602-6. -
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, 10.1007/978-3-319-25040-3_54. -
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, 10.1007/978-3-319-17563-8. -
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:
- MinFEM: A minimal finite element tool for demonstration and teaching. (github.com/msiebenborn/MinFEM.jl)
- MGSS: A multigrid spline smoothing toolbox for high dimensional data analysis. (CRAN.R-project.org/package=mgss)
- MGSS-Grid: Efficient spline smoothing toolbox for high dimensional data on grids. (github.com/SplineSmoothing/MGSS_grid)
-
MultigridShapeOpt: Codes for the publication
Fluid dynamic shape optimization using self-adapting nonlinear extension operators with multigrid preconditioners
. (github.com/MultigridShapeOpt)
Short CV
01/2021 | Positive intermediate evaluation of junior professorship, Universität Hamburg |
Since 02/2018 | Junior Professor(W1) for Optimization and Approximation, Department of Mathematics, Universität Hamburg |
01/2014 - 01/2018 | Postdoc in DFG priority program Software for Exascale Computing(SPPEXA), Univeristät Trier |
01/2014 | Doctor in Mathematics, Universität Trier, with V. Schulz |
11/2010 - 01/2014 | Research Assistant, Department of Mathematics, Universität Trier |
10/2010 | Diploma in Mathematics, Universität Trier |
04/2006 - 10/2010 | Studies of Mathematics with minor Computer Science, Universität Trier |