Markus Grasmair

Associate Professor

Department of Mathematical Sciences

markus.grasmair@ntnu.no

Sentralbygg 2, 1052, Gløshaugen

markus.grasmair@ntnu.no

Markus Grasmair has been associate professor at the Department of Mathematical Sciences since October 2013.

Main areas of research

Inverse problems, mathematical methods in image processing, optimisation.

Academic degrees

Habilitation in Mathematics at the University of Vienna (2011). Thesis: Nonsmooth variational methods in image processing and inverse problems.
PhD in Mathematics at the University of Innsbruck (2006). Thesis: Relaxation of nonlocal integrals with rational integrands.
MSc in Mathematics at the University of Innsbruck (2003). Thesis: Norms on root systems (in German).

Work experience

2012-2013 Substitute professor for Scientific Computing at the Catholic University of Eichstätt-Ingolstadt, Germany.
2009-2012 Assistant professor at the University of Vienna, Austria.
2003-2009 Research assistant at the University of Innsbruck, Austria.

Courses

Scientific, academic and artistic work

Displaying a selection of activities. See all publications in the database

Journal publications

Grasmair, Markus. (2020) Source Conditions for Non-Quadratic Tikhonov Regularization. Numerical Functional Analysis and Optimization.
Grasmair, Markus; Klock, Timo; Naumova, Valeriya. (2018) Adaptive multi-penalty regularization based on a generalized Lasso path. Applied and Computational Harmonic Analysis.
Grasmair, Markus; Li, Housen; Munk, Axel. (2018) Variational multiscale nonparametric regression: Smooth functions. Annales de l'I.H.P. Probabilites et statistiques. vol. 54 (2).
Bauer, Martin; Eslitzbichler, Markus; Grasmair, Markus. (2017) Landmark-guided elastic shape analysis of human character motions. Inverse Problems and Imaging. vol. 11 (4).
Bauer, Martin; Grasmair, Markus; Kirisits, Clemens. (2015) Optical Flow on Moving Manifolds. SIAM Journal of Imaging Sciences. vol. 8 (1).
Grasmair, Markus; Haltmeier, Markus; Scherzer, Otmar. (2011) Necessary and sufficient conditions for linear convergence of l1-regularization. Communications on Pure and Applied Mathematics. vol. 64 (2).
Grasmair, Markus. (2010) Generalized Bregman distances and convergence rates for non-convex regularization methods. Inverse Problems. vol. 26 (11).
Grasmair, Markus; Lenzen, Frank. (2010) Anisotropic total variation filtering. Applied Mathematics and Optimization. vol. 62 (3).
Grasmair, Markus; Haltmeier, Markus; Scherzer, Otmar. (2008) Sparse regularization with l^q penalty term. Inverse Problems. vol. 24 (5).
Grasmair, Markus. (2007) The equivalence of the taut string algorithm and BV-regularization. Journal of Mathematical Imaging and Vision. vol. 27 (1).

Books

Scherzer, Otmar; Grasmair, Markus; Grossauer, Harald; Haltmeier, Markus; Lenzen, Frank. (2009) Variational methods in imaging. Springer. 2009. ISBN 978-0-387-30931-6. Applied mathematical sciences (167).

Part of book/report

Gogineni, Vinay Chakravarthi; Langberg, Geir Severin Rakh Elvatun; Naumova, Valeriya; Nygård, Jan Franz; Nygård, Mari; Grasmair, Markus; Werner, Stefan. (2021) Data-Driven Personalized Cervical Cancer Risk Prediction: A Graph-Perspective. 2021 IEEE Statistical Signal Processing Workshop (SSP).
Grunert, Katrin; Holden, Helge; Grasmair, Markus. (2018) On the Equivalence of Eulerian and Lagrangian Variables for the Two-Component Camassa–Holm System. Current Research in Nonlinear Analysis: In Honor of Haim Brezis and Louis Nirenberg.
Grasmair, Markus; Haltmeier, Markus; Scherzer, Otmar. (2010) Sparsity in Inverse Geophysical Problems. Handbook of Geomathematics.

Competencies

Applied mathematics

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