World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
10643
World Ranking
6410
National Ranking
300

Karl Rohr publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Karl Rohr sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 304 publications — 75th percentile

75% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Karl Rohr D-index placement in Computer Science in 2026

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

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 47 D-Index — 56th percentile

56% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Karl Rohr is affiliated with Heidelberg University in Germany and conducts research primarily in the fields of Computer Science and Medicine. Their work spans across several subfields including Computer Vision and Pattern Recognition, Biophysics, Epidemiology, Artificial Intelligence, and Infectious Diseases.

The research topics covered by Karl Rohr include:

  • Cell Image Analysis Techniques
  • Influenza Virus Research Studies
  • Medical Image Segmentation Techniques
  • AI in Cancer Detection
  • Viral Infections and Outbreaks Research
  • Animal Disease Management and Epidemiology
  • Advanced Neural Network Applications

Karl Rohr's recent papers demonstrate a focus on both computational methods and virology. These publications include:

  • Superadditivity and Convex Optimization for Globally Optimal Cell Segmentation Using Deformable Shape Models, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Morphology-dependent entry kinetics and spread of influenza A virus, 2024, bioRxiv (Cold Spring Harbor Laboratory)
  • Morphology-dependent entry kinetics and spread of influenza A virus, 2025, The EMBO Journal
  • EfficientCellSeg: Efficient Volumetric Cell Segmentation Using Context Aware Pseudocoloring, 2022, arXiv (Cornell University)

Throughout these works, Karl Rohr frequently collaborates with a group of co-authors, including Sarah Peterl, Carmen Maria Lahr, Carl Niklas Schneider, Janis Meyer, and Xenia Podlipensky. Each of these collaborators has contributed to multiple joint publications, indicating ongoing research partnerships.

Publication venues for Karl Rohr's work show a distribution across journals and preprint archives that cover both computational and biomedical research domains. These venues include:

  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • bioRxiv (Cold Spring Harbor Laboratory)
  • The EMBO Journal
  • arXiv (Cornell University)

Best Publications

  • Objective comparison of particle tracking methods

    Nicolas Chenouard;Ihor Smal;Fabrice de Chaumont;Martin Maška;Martin Maška

  • Towards model-based recognition of human movements in image sequences

    K. Rohr

  • Landmark-based elastic registration using approximating thin-plate splines

    K. Rohr;H.S. Stiehl;R. Sprengel;T.M. Buzug

  • An objective comparison of cell-tracking algorithms

    Vladimír Ulman;Martin Maška;Klas E G Magnusson;Olaf Ronneberger

  • A benchmark for comparison of cell tracking algorithms

    Martin Maška;Vladimír Ulman;David Svoboda;Pavel Matula

  • Landmark-Based Image Analysis: Using Geometric and Intensity Models

    Karl Rohr

  • Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge.

    Mitko Veta;Yujing J. Heng;Nikolas Stathonikos;Babak Ehteshami Bejnordi

  • Radial basis functions with compact support for elastic registration of medical images

    M. Fornefett;K. Rohr;H.S. Stiehl

  • Point-Based Elastic Registration of Medical Image Data Using Approximating Thin-Plate Splines

    Karl Rohr;H. Siegfried Stiehl;Rainer Sprengel;Wolfgang Beil

  • Biomechanical modeling of the human head for physically based, nonrigid image registration

    A. Hagemann;K. Rohr;H.S. Stiehl;U. Spetzger

  • Incremental recognition of pedestrians from image sequences

    K. Rohr

  • Long-term cancer survival prediction using multimodal deep learning.

    Luís A Vale-Silva;Karl Rohr

  • Recognizing corners by fitting parametric models

    Karl Rohr

  • On 3D differential operators for detecting point landmarks

    Karl Rohr

  • Localization properties of direct corner detectors

    Karl Rohr

  • Deterministic and probabilistic approaches for tracking virus particles in time-lapse fluorescence microscopy image sequences

    William J. Godinez;Marko Lampe;Stefan Wörz;Barbara Müller

  • Segmentation and Quantification of Human Vessels Using a 3-D Cylindrical Intensity Model

    S.. Worz;K.. Rohr

  • Modelling and identification of characteristic intensity variations

    Karl Rohr

  • A New Class of Elastic Body Splines for Nonrigid Registration of Medical Images

    Jan Kohlrausch;Karl Rohr;H. Siegfried Stiehl

  • Elastic registration of medical images using radial basis functions with compact support

    M. Fornefett;K. Rohr;H.S. Stiehl

  • Landmark-based image analysis

    Karl Rohr

Frequent Co-Authors

Roland Eils
Roland Eils Charité - University Medicine Berlin
Ralf Bartenschlager
Ralf Bartenschlager Heidelberg University
Barbara Müller
Barbara Müller University Hospital Heidelberg
Karsten Rippe
Karsten Rippe German Cancer Research Center
Christoph Schnörr
Christoph Schnörr Heidelberg University
Hans-Ulrich Kauczor
Hans-Ulrich Kauczor Heidelberg University
Jan Ellenberg
Jan Ellenberg European Bioinformatics Institute
David L. Spector
David L. Spector Cold Spring Harbor Laboratory
Katrin Amunts
Katrin Amunts Forschungszentrum Jülich
Thomas Cremer
Thomas Cremer Ludwig-Maximilians-Universität München

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