Dr. techn.

Andreas Langer

Junior Participating Researcher
Institute of Applied Analysis and Numerical Simulation
Numerical Mathematics for High Performance Computing

Contact

+49 711 685-69317

Website

Pfaffenwaldring 57
70569 Stuttgart
Germany
Room: 7.155

Subject

  • Optimization
  • Mathematical image processing
  • Parameter selection
  • Domain decomposition methods for total variation minimization
  • Finite element methods for nonsmooth minimization problems

Academic studies and degrees:

  • 2008-2011 PhD, Johann Radon Institute for Computational and Applied Mathematics - Johannes Kepler University Linz, Austria
  • 2000-2006 Diploma in Technical Mathematics, Johannes Kepler University Linz, Austria

Professional and Academic Career:

  • Since 2014 Postdoc, Institute for Applied Analysis and Numerical Simulation (IANS), University of Stuttgart, Germany
  • 2016-2018 Deputy professor, Institute for Applied Analysis and Numerical Simulation (IANS), University of Stuttgart, Germany
  • 2011-2014 Postdoc, Department of Mathematics and Scientific Computing, University of Graz, Austria
  • 2007-2008 Employee, Treasury Middle Office/RLB OÖ, Linz, Austria
  • 2006-2007 Research assistant, Institute for Analysis/Group Dynamical Systems and Approximation Theory, Johannes Kepler University Linz, Austria

Selected Publications:

  • Langer, A. und Gaspoz, F.: Overlapping domain decomposition methods for total variation denoising, akzeptiert von SIAM Journal on Numerical Analysis, March 2019, 29 pp.
  • Alkämper, M. und Langer, A. Using DUNE-ACFem for non-smooth minimization of bounded variation functions. Archive of Numerical Software 5, 1 (2017), 3-19.
  • Hintermüller, M., Rautenberg, C. N., Wu, T. und Langer, A. Optimal selection of
    the regularization function in a generalized total variation model. Part II: algorithm, its analysis and numerical Tests. Journal of Mathemtical Imaging and Vision 59, 3 (2017), 515-533.
  • Langer, A. Automated parameter selection in the L1-L2-TV model for removing Gaussian plus impulse noise. Inverse Problems 33, (2017), 41.
  • Langer, A. Automated parameter selection for total variation minimization in image restoration. Journal of Mathematical Imaging and Vision 57, 2 (2017), 239-268.
  • Hintermüller, M. und Langer, A. Non-overlapping domain decomposition methods for dual total variation based image denoising. Journal of Scientific Computing 62, 2 (2015), 456-481.
  • Hintermüller, M. und Langer, A. Subspace correction methods for a class of non-smooth and non-additive convex variational problems with mixed L1/ L2 data-fidelity in image processing. SIAM Journal on Imaging Sciences 6, 4 (2013), 2134-2173.
  • Langer, A., Osher, S. und Schönlieb, C.-B. Bregmanized domain decomposition methods for image restoration. Journal of Scientific Computing 54, (2013), 549-576.
  • Fornasier, M., Kim, Y., Langer, A. und Schönlieb, C.-B. Wavelet decomposition method for L2/TV-image deblurring. SIAM Journal on Imaging Sciences 5, 3 (2012), 857-885.
  • Fornasier, M., Langer, A. und Schönlieb, C.-B. A convergent overlapping domain decomposition method for total variation minimization. Numerische Mathematik 116, 4 (2010), 645-685.
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