World's Best Scientists 2026 revealed!
Heiko Neumann

Heiko Neumann

D-Index & Metrics

Computer Science

D-Index
34
Citations
4619
World Ranking
12219
National Ranking
604

Heiko Neumann 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 Heiko Neumann 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: 291 publications — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

Heiko Neumann 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 Heiko Neumann 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: 34 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Overview

Heiko Neumann is affiliated with the University of Ulm in Germany and has contributed research primarily in the fields of Neuroscience and Computer Science. Their work spans several subfields including Cognitive Neuroscience, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Aerospace Engineering, and Artificial Intelligence.

The scientist's research topics of focus include neural dynamics and brain function, visual perception and processing mechanisms, robotics and sensor-based localization, advanced memory and neural computing, human pose and action recognition, robot manipulation and learning, and image and object detection techniques.

Recent publications authored or co-authored by Heiko Neumann illustrate the interdisciplinary nature of their research. These include:

  • Defining gaze patterns for process model literacy - Exploring visual routines in process models with diverse mappings (2022, Expert Systems with Applications)
  • Classifier-Guided Visual Correction of Noisy Labels for Image Classification Tasks (2020, OPen Access Repositorium der Universität Ulm (OPARU) (Ulm University))
  • Convolutional Transformer Fusion Blocks for Multi-Modal Gesture Recognition (2023, IEEE Access)
  • Canonical circuit computations for computer vision (2023, Biological Cybernetics)
  • From Near-Optimal Bayesian Integration to Neuromorphic Hardware: A Neural Network Model of Multisensory Integration (2020, Frontiers in Neurorobotics)

Heiko Neumann has collaborated frequently with a set of co-authors, which include Timo Oess, Marc O. Ernst, Daniel Schmid, Christian Jarvers, and Rüdiger Pryss. These collaborations likely reflect shared research interests and complementary expertise.

The scientist's publications are often found in venues such as OPAL (Open@LaTrobe) hosted by La Trobe University, arXiv from Cornell University, bioRxiv by Cold Spring Harbor Laboratory, PLoS Computational Biology, and Expert Systems with Applications.

Best Publications

  • Ontology-Based Integration of Information — A Survey of Existing Approaches

    Holger Wache;Thomas Vögele;Ubbo Visser;Heiner Stuckenschmidt

  • The role of attention in figure-ground segregation in areas V1 and V4 of the visual cortex.

    Jasper Poort;Florian Raudies;Aurel Wannig;Victor A.F. Lamme

  • Fully Convolutional Region Proposal Networks for Multispectral Person Detection

    Daniel Konig;Michael Adam;Christian Jarvers;Georg Layher

  • A contrast- and luminance-driven multiscale network model of brightness perception

    Luiz Pessoa;Ennio Mingolla;Heiko Neumann

  • Disambiguating Visual Motion Through Contextual Feedback Modulation

    Pierre Bayerl;Heiko Neumann

  • Multiple classifier systems for the classificatio of audio-visual emotional states

    Michael Glodek;Stephan Tschechne;Georg Layher;Martin Schels

  • Recurrent V1-V2 interaction in early visual boundary processing.

    Heiko Neumann;Wolfgang Sepp

  • Generating 3D People in Scenes Without People

    Yan Zhang;Mohamed Hassan;Heiko Neumann;Michael J. Black

  • Bio-inspired computer vision

    N. V. Kartheek Medathati;Heiko Neumann;Guillaume S. Masson;Pierre Kornprobst

  • On event-based optical flow detection.

    Tobias Brosch;Stephan Tschechne;Heiko Neumann

  • Multiscale Binarization of Gene Expression Data for Reconstructing Boolean Networks

    Martin Hopfensitz;Christoph Mussel;Christian Wawra;Markus Maucher

  • Quantification of human body fat tissue percentage by MRI

    Hans-Peter Müller;Florian Raudies;Alexander Unrath;Heiko Neumann

  • Luminance and edge information in grouping: a study using visual search

    Iain D Gilchrist;GW Humphreys;MJ Riddoch;H Neumann

  • High-resolution respiratory self-gated golden angle cardiac MRI: Comparison of self-gating methods in combination with k-t SPARSE SENSE.

    Jan Paul;Evica Divkovic;Stefan Wundrak;Peter Bernhardt

  • Facial expression recognition based on geometric and optical flow features in colour image sequences

    R. Niese;A. Al-Hamadi;A. Farag;H. Neumann

  • Neural mechanisms of cortico-cortical interaction in texture boundary detection: a modeling approach.

    A. Thielscher;H. Neumann

  • Computing with a canonical neural circuits model with pool normalization and modulating feedback

    Tobias Brosch;Heiko Neumann

  • A review and evaluation of methods estimating ego-motion

    Florian Raudies;Heiko Neumann

  • The SenseEmotion Database: A Multimodal Database for the Development and Systematic Validation of an Automatic Pain- and Emotion-Recognition System

    Maria Velana;Sascha Gruss;Georg Layher;Patrick Thiam

  • Perception and Interactive Technologies

    Elisabeth André;Laila Dybkjær;Wolfgang Minker;Heiko Neumann

  • Multi-Modal Pain Intensity Recognition Based on the SenseEmotion Database

    Patrick Thiam;Viktor Kessler;Mohammadreza Amirian;Peter Bellmann

  • A COMPREHENSIVE HEAD POSE AND GAZE DATABASE

    U. Weidenbacher;G. Layher;P.-M. Strauss;H. Neumann

Frequent Co-Authors

Marc O. Ernst
Marc O. Ernst University of Ulm
Friedhelm Schwenker
Friedhelm Schwenker University of Ulm
Hans A. Kestler
Hans A. Kestler University of Ulm
Ennio Mingolla
Ennio Mingolla Northeastern University
Luiz Pessoa
Luiz Pessoa University of Maryland, College Park
Siyu Tang
Siyu Tang ETH Zurich
Günther Palm
Günther Palm University of Ulm
Axel Thielscher
Axel Thielscher Technical University of Denmark
Guillaume S. Masson
Guillaume S. Masson Aix-Marseille University
Martin A. Giese
Martin A. Giese University of Tübingen

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