Munk, Axel, Prof. Dr.
- 1992 Mathematics, University of Göttingen, Diploma, Prof. Dr. Manfred Denker
- 1994 Conferral of doctorate: Mathematics, University of Göttingen, Prof. Dr. Manfred Denker
- 1994 PostDoc SFB 373 'Diskrete Structures in Mathematics', University of Bielefeld
- 1995 DFG Research Fellowship: University of Dresden, Cornell, The Wharton School, Philadelphia
- 1996 - 2000 Assistant Professor, Ruhr University Bochum
- 1999 Habilitation: Mathematics, Ruhr University Bochum
- 2000 Associate Professor for Statistics, University of Siegen
- 2000 - 2002 Associate Professor for Applied Mathematics, University of Paderborn
- 2002 - 2008 Chair for Mathematical Stochastics, University of Göttingen
- since 2009 Felix Bernstein Professor for Mathematical Statistics, University of Göttingen
- since 2010 Max Planck Fellow at the Max Planck Institute for biophysical Chemistry, Göttingen
- M. Behr, C. Holmes, A. Munk: Multiscale blind source separation. The Annals of Statistics, arXiv:1608.07173, to appear (2017).
- H. Ta, J. Keller, M. Haltmeier, S.K. Saka, J. Schmied, F. Opazo, P. Tinnefeld, A. Munk, S.W. Hell: Mapping molecules in scanning far-field fluorescence nanoscopy. Nature Communications 6, doi: 10.1038/ncomms8977 (2015).
- K. Frick, A. Munk, H. Sieling: Multiscale change point inference. Journ. Royal Statist. Society, Ser. B, Discussion paper with rejoinder, 76, 495 (2014).
- S. Huckemann, T. Hotz, A. Munk: Intrinsic shape analysis: Geodesic principal component analysis for riemannian manifolds modulo Lie group actions, Discussion paper with rejoinder. Statistica Sinica, 20, 1 (2010).
- N. Bissantz, T. Hohage, A. Munk, F. Ruymgaart: Convergence rates of general regularization methods for statistical inverse problems and applications. SIAM J. Numerical Analysis, 45, 2610 (2007).
Major Research Interests
I am interested in the development of methods for extracting relevant information from data. This data are complex and often arise from collaborations with lab scientists. My research in mathematical statistics is concerned with tools to equip such methods with statistical error control. The challenge is to make them computationally feasonable at the same hand.
Statistical inverse problems, nonparametric regression, statistical imaging and signal recovery, multiscale testing and estimation, qualitative inference, shape analysis, optimal transport.
fast segmentation algorithms, motion estimation, resampling
Statistics in Biophysics
Statistical methods for single molecule experiments, ion channel recordings, nanoscale fluorescence microscopy. My work on Nanostatistics has been highlighted in the Research Features Magazine.
Other areas of application I have been involved include
Clinical trials: Bioequivalence and noninferiority trials.
Econometrics: microstructure noise models.
Pattern recognition: Analysis of fingerprints.
Homepage Department/Research Group
Selected Recent Publications