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Otmar Scherzer

Otmar Scherzer

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Mathematics
Austria
2026
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Engineering and Technology
Austria
2025

D-Index & Metrics

Mathematics

D-Index
55
Citations
12003
World Ranking
788
National Ranking
10

Engineering and Technology

D-Index
54
Citations
11960
World Ranking
3157
National Ranking
11

Research.com Recognitions

  • 2026 - Research.com Mathematics in Austria Leader Award
  • 2025 - Research.com Engineering and Technology in Austria Leader Award
  • 2025 - Research.com Mathematics in Austria Leader Award
  • 2023 - Research.com Engineering and Technology in Austria Leader Award
  • 2023 - Research.com Mathematics in Austria Leader Award
  • 2022 - Research.com Engineering and Technology in Austria Leader Award

Overview

Otmar Scherzer is affiliated with the University of Vienna in Austria. Their primary research focus lies within the broad field of Engineering, with significant contributions to several specialized subfields, including Biomedical Engineering, Mathematical Physics, Geophysics, Computer Vision and Pattern Recognition, and Radiology, Nuclear Medicine and Imaging.

The main topics addressed in Scherzer's research encompass a range of computational and imaging techniques, notably numerical methods in inverse problems, seismic imaging and inversion techniques, photoacoustic and ultrasonic imaging, sparse and compressive sensing techniques, advanced electron microscopy techniques and applications, seismic waves and analysis, and neural networks and their applications.

Scherzer's publication record includes papers in a variety of scientific venues, with frequent contributions to:

  • arXiv (Cornell University)
  • Inverse Problems
  • Journal of Mathematical Imaging and Vision
  • European Mathematical Society Magazine
  • Journal of Inverse and Ill-Posed Problems

Several recent papers illustrate the breadth of Scherzer's work:

  • "Data driven regularization by projection," 2020, published in Inverse Problems
  • "Fourier reconstruction for diffraction tomography of an object rotated into arbitrary orientations," 2021, published in arXiv (Cornell University)
  • "Adjoint-state method for Hybridizable Discontinuous Galerkin discretization, application to the inverse acoustic wave problem," 2020, published in Computer Methods in Applied Mechanics and Engineering
  • "On convergence rates of adaptive ensemble Kalman inversion for linear ill-posed problems," 2022, published in Numerische Mathematik
  • "Motion reconstruction for optical tomography of trapped objects," 2020, published in Inverse Problems

The frequent coauthors collaborating with Scherzer include:

  • Clemens Kirisits
  • Florian Faucher
  • Leon Frischauf
  • Fabian Parzer
  • Andrea Aspri

This network indicates ongoing collaborative research across various topics related to inverse problems and imaging techniques.

Best Publications

  • Iterative regularization methods for nonlinear ill-posed problems

    Barbara Kaltenbacher;Andreas Neubauer;Otmar Scherzer

  • A convergence analysis of the Landweber iteration for nonlinear ill-posed problems

    Martin Hanke;Andreas Neubauer;Otmar Scherzer

  • Variational Methods in Imaging

    Otmar Scherzer;Markus Grasmair;Harald Grossauer;Markus Haltmeier

  • A convergence rates result for Tikhonov regularization in Banach spaces with non-smooth operators

    B Hofmann;B Kaltenbacher;C Pöschl;O Scherzer

  • Handbook of mathematical methods in imaging

    Otmar Scherzer

  • On convergence rates for the Iteratively regularized Gauss-Newton method

    Barbara Blaschke;Andreas Neubauer;Otmar Scherzer

  • Inverse Problems Light: Numerical Differentiation

    Martin Hanke;Otmar Scherzer

  • Sparse Regularization with l q Penalty Term

    Markus Grasmair;Markus Haltmeier;Otmar Scherzer

  • Convergence Criteria of Iterative Methods Based on Landweber Iteration for Solving Nonlinear Problems

    O. Scherzer

  • Optimal a posteriori parameter choice for Tikhonov regularization for solving nonlinear ill-posed problems

    O. Scherzer;H. W. Engl;K. Kunisch

  • Relations Between Regularization and Diffusion Filtering

    Otmar Scherzer;Joachim Weickert

  • The use of Morozov's discrepancy principle for Tikhonov regularization for solving nonlinear ill-posed problems

    Otmar Scherzer

  • Thermoacoustic tomography with integrating area and line detectors

    P. Burgholzer;C. Hofer;G. Paltauf;M. Haltmeier

  • Thermoacoustic computed tomography with large planar receivers

    M Haltmeier;O Scherzer;P Burgholzer;G Paltauf

  • Filtered backprojection for thermoacoustic computed tomography in spherical geometry

    Markus Haltmeier;Thomas Schuster;Otmar Scherzer

  • A convergence analysis of iterative methods for the solution of nonlinear ill-posed problems under affinely invariant conditions

    Peter Deuflhard;Heinz W Engl;Otmar Scherzer

  • Necessary and sufficient conditions for linear convergence of ℓ1-regularization

    M. Grasmaier;M. Haltmeier;O. Scherzer

  • Factors influencing the ill-posedness of nonlinear problems

    B Hofmann;O Scherzer

  • Denoising with higher order derivatives of bounded variation and an application to parameter estimation

    O. Scherzer

  • Error estimates for non-quadratic regularization and the relation to enhancement

    Elena Resmerita;Otmar Scherzer

  • Weakly Differentiable Functions

    Otmar Scherzer;Markus Grasmair;Harald Grossauer;Markus Haltmeier

Frequent Co-Authors

Markus Haltmeier
Markus Haltmeier University of Innsbruck
Maarten V. de Hoop
Maarten V. de Hoop Rice University
Barbara Kaltenbacher
Barbara Kaltenbacher University of Klagenfurt
Ian Frigaard
Ian Frigaard University of British Columbia
Bert Jüttler
Bert Jüttler Johannes Kepler University of Linz
Heinz W. Engl
Heinz W. Engl University of Vienna
Martin Hanke
Martin Hanke Johannes Gutenberg University of Mainz
Joachim Weickert
Joachim Weickert Saarland University
Adrian Constantin
Adrian Constantin University of Vienna
Ulrich Ansorge
Ulrich Ansorge University of Vienna

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