World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
53
Citations
9432
World Ranking
4893
National Ranking
2273

Naoki Masuda 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 Naoki Masuda 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: 241 publications — 60th percentile

60% of scientists in this discipline score the same or lower.

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

Naoki Masuda 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 Naoki Masuda 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: 53 D-Index — 67th percentile

67% of scientists in this discipline score the same or lower.

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

Overview

Naoki Masuda is affiliated with the University at Buffalo, State University of New York in the United States. Their research spans significant contributions in physics, astronomy, and medicine, with a particular focus on statistical and nonlinear physics and cognitive neuroscience. Masuda's work engages deeply with complex network analysis techniques and functional brain connectivity studies, among other topics.

The scientist's main fields of study include:

  • Physics and Astronomy
  • Medicine

Subfields of study encompass:

  • Statistical and Nonlinear Physics
  • Cognitive Neuroscience
  • Sociology and Political Science
  • Cardiology and Cardiovascular Medicine
  • Molecular Biology

Main topics of Masuda's work consist of:

  • Complex Network Analysis Techniques
  • Opinion Dynamics and Social Influence
  • Evolutionary Game Theory and Cooperation
  • Functional Brain Connectivity Studies
  • Mental Health Research Topics
  • Neural dynamics and brain function
  • Complex Systems and Time Series Analysis

Masuda has contributed to several recent papers including:

  • "Closer to critical resting-state neural dynamics in individuals with higher fluid intelligence," 2020, Communications Biology
  • "Formation of Calcified Nodule as a Cause of Early In-Stent Restenosis in Patients Undergoing Dialysis," 2020, Journal of the American Heart Association
  • "Detecting anomalous citation groups in journal networks," 2021, Scientific Reports
  • "Focused attention meditation changes the boundary and configuration of functional networks in the brain," 2020, Scientific Reports
  • "Disrupted brain connectivity in children treated with therapeutic hypothermia for neonatal encephalopathy," 2021, NeuroImage Clinical

Frequent collaborators in Masuda's research include Neil G. MacLaren, Takamitsu Watanabe, Ruodan Liu, Nobuhiko Ogata, and Elohim Fonseca dos Reis.

The venues where Masuda has most frequently published their work include:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
  • Scientific Reports
  • Physical Review Research

In addition to journal articles, Masuda has a book publication titled A Guide to Temporal Networks (2020), published under the Complexity Science Series.

Best Publications

  • Random walks and diffusion on networks

    Naoki Masuda;Mason A. Porter;Mason A. Porter;Renaud Lambiotte

  • Cryptosystems with discretized chaotic maps

    N. Masuda;K. Aihara

  • A Guide to Temporal Networks

    Naoki Masuda;Renaud Lambiotte

  • Spatial prisoner's dilemma optimally played in small-world networks

    Naoki Masuda;Kazuyuki Aihara

  • Predicting and controlling infectious disease epidemics using temporal networks

    Naoki Masuda;Petter Holme;Petter Holme;Petter Holme

  • Participation costs dismiss the advantage of heterogeneous networks in evolution of cooperation.

    Naoki Masuda

  • A pairwise maximum entropy model accurately describes resting-state human brain networks

    Takamitsu Watanabe;Satoshi Hirose;Hiroyuki Wada;Yoshio Imai

  • Temporal Networks: Slowing Down Diffusion by Long Lasting Interactions

    Naoki Masuda;Konstantin Klemm;Víctor M. Eguíluz

  • Systematic analysis of neural projections reveals clonal composition of the Drosophila brain.

    Masayoshi Ito;Naoki Masuda;Kazunori Shinomiya;Keita Endo

  • Energy landscape analysis of neuroimaging data

    Takahiro Ezaki;Takamitsu Watanabe;Masayuki Ohzeki;Naoki Masuda

  • Global and local synchrony of coupled neurons in small-world networks

    Naoki Masuda;Kazuyuki Aihara

  • Atypical intrinsic neural timescale in autism.

    Takamitsu Watanabe;Geraint Rees;Naoki Masuda

  • Chaotic block ciphers: from theory to practical algorithms

    N. Masuda;G. Jakimoski;K. Aihara;L. Kocarev

  • Heterogeneous voter models

    Naoki Masuda;Naoki Masuda;N. Gibert;N. Gibert;S. Redner

  • Bursty Communication Patterns Facilitate Spreading in a Threshold-Based Epidemic Dynamics

    Taro Takaguchi;Naoki Masuda;Petter Holme;Petter Holme;Petter Holme

  • Multi-state epidemic processes on complex networks

    Naoki Masuda;Norio Konno

  • Detecting sequences of system states in temporal networks.

    Naoki Masuda;Petter Holme

  • Geographical threshold graphs with small-world and scale-free properties.

    Naoki Masuda;Hiroyoshi Miwa;Norio Konno

  • Temporal Network Epidemiology

    Naoki Masuda;Petter Holme

  • Predictability of Conversation Partners

    Taro Takaguchi;Mitsuhiro Nakamura;Nobuo Sato;Kazuo Yano

  • Clustering Coefficients for Correlation Networks.

    Naoki Masuda;Michiko Sakaki;Takahiro Ezaki;Takamitsu Watanabe

  • Formation of feedforward networks and frequency synchrony by spike-timing-dependent plasticity

    Naoki Masuda;Hiroshi Kori

  • A Guide to Temporal Networks, 2nd edition

    Naoki Masuda;Renaud Lambiotte

Frequent Co-Authors

Norio Konno
Norio Konno Yokohama National University
Kazuyuki Aihara
Kazuyuki Aihara University of Tokyo
Petter Holme
Petter Holme Aalto University
Renaud Lambiotte
Renaud Lambiotte University of Oxford
Mason A. Porter
Mason A. Porter University of California, Los Angeles
Khalid Hamandi
Khalid Hamandi Cardiff University
Krish D. Singh
Krish D. Singh Cardiff University
Shun-ichi Amari
Shun-ichi Amari RIKEN Center for Brain Science
Kou Murayama
Kou Murayama University of Reading
Geraint Rees
Geraint Rees University College London

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