World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
34
Citations
16109
World Ranking
2839
National Ranking
175

Overview

Martin Hanke is affiliated with Johannes Gutenberg University of Mainz in Germany. Their research primarily spans the field of engineering, with particular focus on several subfields including electrical and electronic engineering, mathematical physics, materials chemistry, geophysics, and biomedical engineering.

The scientist's work covers multiple specialized topics, notably:

  • Numerical methods in inverse problems
  • Seismic imaging and inversion techniques
  • Block copolymer self-assembly
  • Electrostatics and colloid interactions
  • Advanced mathematical modeling in engineering
  • Electric motor design and analysis
  • Topology optimization in engineering

Martin Hanke has coauthored several papers with frequent collaborators such as Marvin P. Bernhardt, Nico F. A. van der Vegt, Georg Reuber, L. Holbach, and Alexander A. Popov.

Selected recent publications by Martin Hanke include:

  • "Mathematical analysis of some iterative methods for the reconstruction of memory kernels", 2021, ETNA - Electronic Transactions on Numerical Analysis
  • "Unique Solvability of a System of Ordinary Differential Equations Modeling a Warm Cloud Parcel", 2020, SIAM Journal on Applied Mathematics
  • "Inferring rheology and geometry of subsurface structures by adjoint-based inversion of principal stress directions", 2020, Geophysical Journal International
  • "Iterative integral equation methods for structural coarse-graining", 2021, The Journal of Chemical Physics
  • "Stability, Speed, and Constraints for Structural Coarse-Graining in VOTCA", 2023, Journal of Chemical Theory and Computation

The publication venues where Martin Hanke has featured frequently include:

  • arXiv (Cornell University)
  • Geophysical Journal International
  • The Journal of Chemical Physics
  • Journal of Chemical Theory and Computation
  • ETNA - Electronic Transactions on Numerical Analysis

Best Publications

  • Regularization of Inverse Problems

    Heinz W. Engl;Martin Hanke;Andreas Neubauer

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

    Martin Hanke;Andreas Neubauer;Otmar Scherzer

  • Regularization methods for large-scale problems

    Martin Hanke;Per Christian Hansen

  • Conjugate Gradient Type Methods for Ill-Posed Problems

    Martin Hanke

  • A regularizing Levenberg - Marquardt scheme, with applications to inverse groundwater filtration problems

    Martin Hanke

  • Numerical implementation of two noniterative methods for locating inclusions by impedance tomography

    Martin Brühl;Martin Hanke

  • Inverse Problems Light: Numerical Differentiation

    Martin Hanke;Otmar Scherzer

  • Limitations of the L-curve method in ill-posed problems

    Martin Hanke

  • Recent progress in electrical impedance tomography

    Martin Hanke;Martin Brühl

  • Accelerated Landweber iterations for the solution of ill-posed equations

    Martin Hanke

  • Nonstationary iterated Tikhonov regularization

    M. Hanke;C. W. Groetsch

  • Regularizing properties of a truncated Newton-CG algorithm for nonlinear inverse problems

    Martin Hanke

  • A direct impedance tomography algorithm for locating small inhomogeneities

    Martin Brühl;Martin Hanke;Michael S. Vogelius

  • Preconditioned iterative regularization for Ill-posed problems

    Martin Hanke;James Nagy;Robert Plemmons

  • Iterative Reconstruction of Memory Kernels

    Gerhard Jung;Martin Hanke;Friederike Schmid

  • A general heuristic for choosing the regularization parameter in ill-posed problems

    Martin Hanke;Toomas Raus

  • Restoration of atmospherically blurred images by symmetric indefinite conjugate gradient techniques

    Martin Hanke;James G Nagy

  • On Lanczos based methods for the regularization of discrete ill-posed problems

    Martin Hanke

  • On the acceleration of Kaczmarz's method for inconsistent linear systems

    Martin Hanke;Wilhelm Niethammer

  • Crack detection using electrostatic measurements

    Martin Brühl;Martin Hanke;Michael Pidcock

Frequent Co-Authors

Heinz W. Engl
Heinz W. Engl University of Vienna
Otmar Scherzer
Otmar Scherzer University of Vienna
James G. Nagy
James G. Nagy Emory University
Michael Neumann
Michael Neumann University of Connecticut
Michael A. Saunders
Michael A. Saunders Stanford University
Raymond H. Chan
Raymond H. Chan Lingnan University
Habib Ammari
Habib Ammari ETH Zurich
Michele Benzi
Michele Benzi Scuola Normale Superiore di Pisa
Jan S. Hesthaven
Jan S. Hesthaven Karlsruhe Institute of Technology
Boris J. P. Kaus
Boris J. P. Kaus Johannes Gutenberg University of Mainz

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