World's Best Scientists 2026 revealed!
Fred A. Hamprecht

Fred A. Hamprecht

D-Index & Metrics

Computer Science

D-Index
57
Citations
16034
World Ranking
3779
National Ranking
168

Fred A. Hamprecht 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 Fred A. Hamprecht 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: 234 publications — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Fred A. Hamprecht 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 Fred A. Hamprecht 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: 57 D-Index — 74th percentile

74% of scientists in this discipline score the same or lower.

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

Overview

Fred A. Hamprecht is affiliated with Heidelberg University in Germany, contributing extensively to research at the intersection of biochemistry, genetics, molecular biology, and computer science. Their work spans multiple subfields, including molecular biology, computer vision and pattern recognition, plant science, biophysics, and artificial intelligence.

Hamprecht's research primarily focuses on several core topics:

  • Cell Image Analysis Techniques
  • Single-cell and spatial transcriptomics
  • Plant Molecular Biology Research
  • Advanced Image and Video Retrieval Techniques
  • Advanced Neural Network Applications
  • Smart Agriculture and AI
  • Plant Reproductive Biology

The scientist has published a significant number of papers in various venues. Frequent publication outlets include:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Lecture Notes in Computer Science
  • eLife

Selected recent publications by Hamprecht include:

  • "Accurate and versatile 3D segmentation of plant tissues at cellular resolution," 2020, eLife
  • "A digital 3D reference atlas reveals cellular growth patterns shaping the Arabidopsis ovule," 2021, eLife
  • "Seipin forms a flexible cage at lipid droplet formation sites," 2022, Nature Structural & Molecular Biology
  • "The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning," 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Temporal control of the integrated stress response by a stochastic molecular switch," 2022, Science Advances

Collaboration is a notable aspect of Hamprecht's research activity. Frequent co-authors who have contributed to their work include:

  • Lorenzo Cerrone
  • Anna Kreshuk
  • Athul Vijayan
  • Kay Schneitz
  • Adrian Wolny

Best Publications

  • ilastik: interactive machine learning for (bio)image analysis.

    Stuart Berg;Dominik Kutra;Thorben Kroeger;Christoph N Straehle

  • A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data

    Bjoern H Menze;B Michael Kelm;Ralf Masuch;Uwe Himmelreich

  • Ilastik: Interactive learning and segmentation toolkit

    Christoph Sommer;Christoph Straehle;Ullrich Kothe;Fred A. Hamprecht

  • An objective comparison of cell-tracking algorithms

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

  • On the Spectral Bias of Neural Networks

    Nasim Rahaman;Aristide Baratin;Devansh Arpit;Felix Draxler

  • Learning Steerable Filters for Rotation Equivariant CNNs

    Maurice Weiler;Fred A. Hamprecht;Martin Storath

  • Accurate and versatile 3D segmentation of plant tissues at cellular resolution

    Adrian Wolny;Lorenzo Cerrone;Athul Vijayan;Rachele Tofanelli

  • A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems

    Jorg H. Kappes;Bjoern Andres;Fred A. Hamprecht;Christoph Schnorr

  • Three-dimensional quantitative similarity-activity relationships (3D QSiAR) from SEAL similarity matrices.

    Hugo Kubinyi;Fred A. Hamprecht;Thomas Mietzner

  • On oblique random forests

    Bjoern H. Menze;B. Michael Kelm;Daniel N. Splitthoff;Ullrich Koethe

  • Robust prediction of the MASCOT score for an improved quality assessment in mass spectrometric proteomics

    Thomas Koenig;Bjoern H. Menze;Marc Kirchner;Flavio Monigatti

  • Multi-modal Brain Tumor Segmentation using Deep Convolutional Neural Networks

    G. Urban;M. Bendszus;F. A. Hamprecht;J. Kleesiek

  • A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems

    Jörg H. Kappes;Bjoern Andres;Fred A. Hamprecht;Christoph Schnörr

  • Learning to count with regression forest and structured labels

    Luca Fiaschi;Ullrich Koethe;Rahul Nair;Fred A. Hamprecht

  • Essentially No Barriers in Neural Network Energy Landscape

    Felix Draxler;Kambis Veschgini;Manfred Salmhofer;Fred A. Hamprecht

  • Visualizing a homogeneous blend in bulk heterojunction polymer solar cells by analytical electron microscopy.

    Martin Pfannmöller;Harald Flügge;Gerd Benner;Irene Wacker

  • Imagining the future of bioimage analysis

    Erik Meijering;Anne E Carpenter;Hanchuan Peng;Fred A Hamprecht

  • Multicut brings automated neurite segmentation closer to human performance

    Thorsten Beier;Constantin Pape;Nasim Rahaman;Timo Prange

  • Automated detection and segmentation of synaptic contacts in nearly isotropic serial electron microscopy images.

    Anna Kreshuk;Christoph N. Straehle;Christoph Sommer;Ullrich Koethe

  • Concise Representation of Mass Spectrometry Images by Probabilistic Latent Semantic Analysis

    Michael Hanselmann;Marc Kirchner;Bernhard Y. Renard;Erika R. Amstalden

  • Author response: Accurate and versatile 3D segmentation of plant tissues at cellular resolution

    Adrian Wolny;Adrian Wolny;Lorenzo Cerrone;Athul Vijayan;Rachele Tofanelli

  • A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data

    Bjoern Holger Menze;Bernd Michael Kelm;Ralf Masuch;Uwe Himmerlreich

Frequent Co-Authors

Bjoern H. Menze
Bjoern H. Menze University of Zurich
Bernhard Y. Renard
Bernhard Y. Renard Hasso Plattner Institute
Hanno Steen
Hanno Steen Boston Children's Hospital
Graham Knott
Graham Knott École Polytechnique Fédérale de Lausanne
Bernd Jähne
Bernd Jähne Heidelberg University
Christoph Schnörr
Christoph Schnörr Heidelberg University
Steeve Boulant
Steeve Boulant University of Florida
Albert Cardona
Albert Cardona University of Cambridge
Boaz Nadler
Boaz Nadler Weizmann Institute of Science
Erik Agrell
Erik Agrell Chalmers University of Technology

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