Ulrich Böttcher geb. HartleifWorkgroup Prof. Dr. Benedikt WirthInstitute for Computational and Applied Mathematics University of Münster Einsteinstrasse 62 D-48149 Münster ContactOffice room: Orleans-Ring 12, SRZ 330Phone: +49 251 83-33721 e-mail: |
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Research Interests:
- Image Segmentation and image reconsctruvtion using curvature-like regularizers
- Variational Methods
- Numerical Modelling and Simulation
- Object detection in biological microscopy data
Short CV
| Jan 2019 |
Scientific Researcher and PhD student Workgroup Mathematical Optimization of Prof. Dr. Benedikt Wirth Institute for Computational and Applied Mathematics, WWU Münster |
| Apr 2012 - Nov 2014 |
Master of Science in Mathematics at WWU Münster Master Thesis: An Ambrosio-Tortorelli Functional for Segmentation of 3D Images with Poisson Noise Supervisor: Prof. Dr. Martin Burger |
| Apr 2009 - Mar 2012 |
Bachelor of Science in Mathematics at Johannes Gutenberg-Universität Mainz Bachelor Thesis: Konvergenbeschleunigung von Vektorfolgen mittels Minimalolynon-Extrapolation Supervisor: Prf. Dr. Thorsten Raasch |
Teaching
| Winter 2014/15 | Tutorials: Optimization I |
| Summer 2015 | Tutorials: Optimization II |
| Winter 2015/16 | Practical course: Introduction into programming with MATLAB |
| Summer 2016 | Practical course: Introduction into programming with MATLAB |
| Winter 2016/17 | Practical course: Introduction into programming with MATLAB |
| Summer 2017 | Tutorials: Optimization I |
| Summer 2018 | Tutorials: Optimization I |
Conferences
| Jun 2018 | SIAM Conference on Imaging Science, Bologna, Italy |
| Jan 2018 | MIA Mathematics and Images Analysis, Berlin, Germany |
| Feb-Mar 2017 | 3rd Applied Mathematics Symposium Münster: Shape, Images and Optimization, Münster, Germany |
| Mar 2016 | SIAM Conference on Imaging Science, Albuquerque, New Mexico, USA |
| Sep 2015 | 1st Applied Mathematics Symposium Münster: Variational Methods for Dynamic Inverse Problems and Imaging, Münster, Germany |
Publications
- U. Böttcher, B. Wirth. Convex lifting-type methods for curvature regularization. Accepted at Variational methods for nonlinear geometric data and applications, editors: P. Grohs, M. Holler, A. Weinmann, Springer, 2020 (to be published).