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Computer Science
Austria
2026

D-Index & Metrics

Computer Science

D-Index
78
Citations
28302
World Ranking
1188
National Ranking
9

Wolfgang Maass 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 Wolfgang Maass 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: 329 publications — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Wolfgang Maass 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 Wolfgang Maass 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: 78 D-Index — 92nd percentile

92% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2026 - Research.com Computer Science in Austria Leader Award
  • 2025 - Research.com Computer Science in Austria Leader Award
  • 2023 - Research.com Computer Science in Austria Leader Award
  • 2022 - Research.com Computer Science in Austria Leader Award
  • 2013 - Member of Academia Europaea

Overview

Wolfgang Maass is affiliated with Graz University of Technology in Austria. Their research spans several fields including Engineering, Neuroscience, and Computer Science, with a particular focus on Electrical and Electronic Engineering, Cognitive Neuroscience, and Artificial Intelligence. Their work often contributes to advanced studies in neural and computational systems.

The primary topics in Maass's research include:

  • Advanced Memory and Neural Computing
  • Neural dynamics and brain function
  • Ferroelectric and Negative Capacitance Devices
  • Neural Networks and Reservoir Computing
  • Neural Networks and Applications
  • CCD and CMOS Imaging Sensors
  • EEG and Brain-Computer Interfaces

Frequent publication venues for Maass's work include:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • arXiv (Cornell University)
  • Nature Communications
  • Nature Machine Intelligence
  • Proceedings of the IEEE

Some of the recent papers published by Maass or closely related to their research collaborations are:

  • "Embedded Devices for Neuromorphic Time-Series Assessment" (2022), Maryland Shared Open Access Repository (USMAI Consortium)
  • "A solution to the learning dilemma for recurrent networks of spiking neurons" (2020), Nature Communications
  • "Optimized spiking neurons can classify images with high accuracy through temporal coding with two spikes" (2021), Nature Machine Intelligence
  • "A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware" (2022), Nature Machine Intelligence
  • "Brain computation by assemblies of neurons" (2020), Proceedings of the National Academy of Sciences

Maass has collaborated frequently with several researchers in their field, including:

  • Franz Scherr
  • Robert Legenstein
  • Anand Subramoney
  • Guillaume Bellec
  • Ceca Kraišniković

In 2013, Wolfgang Maass was recognized as a Member of Academia Europaea.

Best Publications

  • Real-time computing without stable states: a new framework for neural computation based on perturbations

    Wolfgang Maass;Thomas Natschläger;Henry Markram

  • Pulsed Neural Networks

    Wolfgang Maass;Christopher M. Bishop

  • State-dependent computations: spatiotemporal processing in cortical networks

    Dean V. Buonomano;Wolfgang Maass

  • Approximation schemes for covering and packing problems in image processing and VLSI

    Dorit S. Hochbaum;Wolfgang Maass

  • 2007 Special Issue: Edge of chaos and prediction of computational performance for neural circuit models

    Robert Legenstein;Wolfgang Maass

  • Neural dynamics as sampling: a model for stochastic computation in recurrent networks of spiking neurons.

    Lars Buesing;Johannes Bill;Bernhard Nessler;Wolfgang Maass

  • A solution to the learning dilemma for recurrent networks of spiking neurons

    Guillaume Emmanuel Fernand Bellec;Franz Scherr;Anand Subramoney;Elias Hajek

  • Threshold circuits of bounded depth

    András Hajnal;András Hajnal;Wolfgang Maass;Wolfgang Maass;Pavel Pudlák;Pavel Pudlák;György Turán;György Turán

  • On the Computational Power of Winner-Take-All

    Wolfgang Maass

  • Threshold circuits of bounded depth

    Andras Hajnal;Wolfgang Maass;Pavel Pudlak;Mario Szegedy

  • On the computational power of circuits of spiking neurons

    Wolfgang Maass;Henry Markram

  • Towards a theoretical foundation for morphological computation with compliant bodies

    Helmut Hauser;Auke J. Ijspeert;Rudolf M. Füchslin;Rolf Pfeifer

  • Lower bounds for the computational power of networks of spiking neurons

    Wolfgang Maass

  • A Learning Theory for Reward-Modulated Spike-Timing-Dependent Plasticity with Application to Biofeedback

    Robert A. Legenstein;Dejan Pecevski;Wolfgang Maass

  • Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity

    Bernhard Nessler;Michael Pfeiffer;Michael Pfeiffer;Lars Buesing;Wolfgang Maass

  • The "Liquid Computer": A Novel Strategy for Real-Time Computing on Time Series

    T. Natschläger;W. Maass;H. Markram

  • Computational aspects of feedback in neural circuits

    Wolfgang Maass;Prashant Joshi;Eduardo D. Sontag

  • Fast sigmoidal networks via spiking neurons

    Wolfgang Maass

  • What Can a Neuron Learn with Spike-Timing-Dependent Plasticity?

    Robert Legenstein;Christian Naeger;Wolfgang Maass

  • Long short-term memory and Learning-to-learn in networks of spiking neurons

    Guillaume Emmanuel Fernand Bellec;Darjan Salaj;Anand Subramoney;Robert Legenstein

  • Networks of Spiking Neurons: The Third Generation of Neural Network Models

    Wolfgang Maass

Frequent Co-Authors

Robert Legenstein
Robert Legenstein Graz University of Technology
Henry Markram
Henry Markram École Polytechnique Fédérale de Lausanne
Christos H. Papadimitriou
Christos H. Papadimitriou Columbia University
Eduardo D. Sontag
Eduardo D. Sontag Northeastern University
Michael Pfeiffer
Michael Pfeiffer Bosch Center for Artificial Intelligence
Santosh Vempala
Santosh Vempala Georgia Institute of Technology
Peter Auer
Peter Auer University of Leoben
Gerhard Neumann
Gerhard Neumann Karlsruhe Institute of Technology
Auke Jan Ijspeert
Auke Jan Ijspeert École Polytechnique Fédérale de Lausanne

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