World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
42
Citations
6820
World Ranking
1802
National Ranking
107

Axel Munk publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Axel Munk sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 83 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 257 publications — 78th percentile

78% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

Axel Munk D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Axel Munk sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 138 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 42 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

Overview

Axel Munk is a researcher affiliated with the University of Göttingen in Germany. Their work primarily spans the fields of Mathematics and Biochemistry, Genetics and Molecular Biology. Munk's research subfields include Statistics and Probability, Biophysics, Applied Mathematics, Molecular Biology, and Artificial Intelligence.

The scientist's research topics cover a broad range of areas related to statistical methods, mathematical theory, and biological applications. Notable main research topics include Statistical Methods and Inference, Markov Chains and Monte Carlo Methods, Advanced Fluorescence Microscopy Techniques, Point Processes and Geometric Inequalities, Cell Image Analysis Techniques, Geometric Analysis and Curvature Flows, and Bayesian Methods and Mixture Models.

Munk has published extensively, with frequent publication venues including arXiv (Cornell University), SIAM Journal on Mathematics of Data Science, The Annals of Statistics, bioRxiv (Cold Spring Harbor Laboratory), and Nature Computational Science. This indicates a strong presence in both preprint and peer-reviewed journals spanning statistics, mathematics, and computational science.

Recent papers authored or co-authored by Munk demonstrate a focus on statistical methodology and applications in computational sciences:

  • Seeded binary segmentation: a general methodology for fast and optimal changepoint detection, 2022, Biometrika
  • Colocalization for super-resolution microscopy via optimal transport, 2021, Nature Computational Science
  • Testing for dependence on tree structures, 2020, Proceedings of the National Academy of Sciences
  • Empirical Regularized Optimal Transport: Statistical Theory and Applications, 2020, SIAM Journal on Mathematics of Data Science
  • Multiscale Quantile Segmentation, 2020, Journal of the American Statistical Association

The scientist has collaborated frequently with several colleagues. The most recurrent co-authors include Housen Li, Marcel Klatt, Shayan Hundrieser, Thomas Staudt, and Frank Werner. These collaborations reflect a network of researchers working at the intersection of mathematics, statistics, and computational biology.

Best Publications

  • Multiscale change point inference

    Klaus Frick;Axel Munk;Axel Munk;Hannes Sieling

  • Box-Type Approximations in Nonparametric Factorial Designs

    Edgar Brunner;Holger Dette;Axel Munk

  • Convergence rates of general regularization methods for statistical inverse problems and applications

    Nicolai Bissantz;T. Hohage;Axel Munk;F. Ruymgaart

  • INTRINSIC SHAPE ANALYSIS: GEODESIC PCA FOR RIEMANNIAN MANIFOLDS MODULO ISOMETRIC LIE GROUP ACTIONS

    Stephan Huckemann;Thomas Hotzand;Axel Munk;Georgia Augusta

  • Consistencies and rates of convergence of jump-penalized least squares estimators

    Leif Boysen;Angela Kempe;Volkmar Liebscher;Axel Munk

  • Estimating the variance in nonparametric regression—what is a reasonable choice?

    H. Dette;A. Munk;T. Wagner

  • Inference for empirical Wasserstein distances on finite spaces

    Max Sommerfeld;Axel Munk;Axel Munk

  • Intrinsic shape analysis: Geodesic principal component analysis for Riemannian manifolds modulo Lie group actions. Discussion paper with rejoinder.

    S. Huckemann;T. Hotz;A. Munk

  • Testing heteroscedasticity in nonparametric regression

    H. Dette;A. Munk

  • Nonparametric validation of similar distributions and assessment of goodness of fit

    Axel Munk;Claudia Czado

  • An unbiased test for the bioequivalence problem

    Lawrence D. Brown;J. T. Gene Hwang;Axel Munk

  • Hidden Markov models for circular and linear-circular time series

    Hajo Holzmann;Axel Munk;Max Suster;Walter Zucchini

  • Identifiability of Finite Mixtures of Elliptical Distributions

    Hajo Holzmann;Axel Munk;Tilmann Gneiting

  • Consistency and rates of convergence of nonlinear Tikhonov regularization with random noise

    Nicolai Bissantz;Thorsten Hohage;Axel Munk

  • Validation of linear regression models

    Holger Dette;Axel Munk

  • Nonparametric comparison of several regression functions: exact and asymptotic theory

    Axel Munk;Holger Dette

  • Global Models for the Orientation Field of Fingerprints: An Approach Based on Quadratic Differentials

    S. Huckemann;T. Hotz;A. Munk

  • Contributions of empirical and quantile processes to the asymptotic theory of goodness-of-fit tests

    Eustasio del Barrio;Juan A. Cuesta-Albertos;Carlos Matrán;Sándor Csörgö

  • On difference‐based variance estimation in nonparametric regression when the covariate is high dimensional

    Axel Munk;Nicolai Bissantz;Thorsten Wagner;Gudrun Freitag

  • Non-parametric confidence bands in deconvolution density estimation

    Nicolai Bissantz;Lutz Dümbgen;Hajo Holzmann;Axel Munk

Frequent Co-Authors

Holger Dette
Holger Dette Ruhr University Bochum
Markus Haltmeier
Markus Haltmeier University of Innsbruck
Claudia Steinem
Claudia Steinem University of Göttingen
Thorsten Hohage
Thorsten Hohage University of Göttingen
Claudia Czado
Claudia Czado Technical University of Munich
Bert L. de Groot
Bert L. de Groot Max Planck Society
Martin Korte
Martin Korte Technische Universität Braunschweig
Joachim Weickert
Joachim Weickert Saarland University
Stefan W. Hell
Stefan W. Hell Max Planck Society

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