World's Best Scientists 2026 revealed!
Hiroshi Motoda

Hiroshi Motoda

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Computer Science
Japan
2025

D-Index & Metrics

Computer Science

D-Index
45
Citations
24031
World Ranking
6976
National Ranking
99

Hiroshi Motoda 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 Hiroshi Motoda 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.

Hiroshi Motoda 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 Hiroshi Motoda 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: 45 D-Index — 51st percentile

51% 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

  • 2025 - Research.com Computer Science in Japan Leader Award
  • 2022 - Research.com Computer Science in Japan Leader Award

Overview

Hiroshi Motoda is affiliated with Osaka University in Japan. Their research spans multiple fields, primarily focusing on computer science, physics and astronomy, and social sciences.

The main research topics covered by their work include:

  • Complex Network Analysis Techniques
  • Graph theory and applications
  • Transportation Planning and Optimization
  • Bioinformatics and Genomic Networks
  • Network Security and Intrusion Detection
  • Anomaly Detection Techniques and Applications
  • Data Stream Mining Techniques

Motoda's scholarly contributions include papers published mainly in the venues Social Network Analysis and Mining and Intelligent Data Analysis. Notable recent publications are:

  • Efficient computation of target-oriented link criticalness centrality in uncertain graphs, 2021, Intelligent Data Analysis
  • Efficient computation of expected motif frequency in uncertain graphs by exploiting possible world marginalization and motif transition, 2022, Social Network Analysis and Mining
  • Constructing outlier-free histograms with variable bin-width based on distance minimization, 2023, Intelligent Data Analysis
  • General framework of opening and closing shops over a spatial network based on stochastic utility under competitive and time-bounded environment, 2021, Social Network Analysis and Mining

Their collaboration network includes frequent coauthors such as Takayasu Fushimi, Kazumi Saito, Kouzou Ohara, Masahiro Kimura, and João Gama.

Motoda has also contributed to book publications with Springer Science+Business Media, including titles such as Advances in Knowledge Discovery and Data Mining published in 2022.

Best Publications

  • Top 10 algorithms in data mining

    Xindong Wu;Vipin Kumar;J. Ross Quinlan;Joydeep Ghosh

  • Feature Selection for Knowledge Discovery and Data Mining

    Huan Liu;Hiroshi Motoda

  • Computational Methods of Feature Selection

    Huan Liu;Hiroshi Motoda

  • An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data

    Akihiro Inokuchi;Takashi Washio;Hiroshi Motoda

  • Feature Extraction, Construction and Selection: A Data Mining Perspective

    Huan Liu;Hiroshi Motoda

  • A flash-memory based file system

    Atsuo Kawaguchi;Shingo Nishioka;Hiroshi Motoda

  • State of the art of graph-based data mining

    Takashi Washio;Hiroshi Motoda

  • Feature Extraction, Construction and Selection

    Huan Liu;Hiroshi Motoda

  • Feature Selection: An Ever Evolving Frontier in Data Mining

    Huan Liu;Hiroshi Motoda;Rudy Setiono;Zheng Zhao

  • Complete Mining of Frequent Patterns from Graphs: Mining Graph Data

    Akihiro Inokuchi;Takashi Washio;Hiroshi Motoda

  • Consistency Based Feature Selection

    Manoranjan Dash;Huan Liu;Hiroshi Motoda

  • Instance Selection and Construction for Data Mining

    Huan Liu;Hiroshi Motoda

  • Blocking links to minimize contamination spread in a social network

    Masahiro Kimura;Kazumi Saito;Hiroshi Motoda

  • On Issues of Instance Selection

    Huan Liu;Hiroshi Motoda

  • Extracting influential nodes on a social network for information diffusion

    Masahiro Kimura;Kazumi Saito;Ryohei Nakano;Hiroshi Motoda

  • Rough Sets and Intelligent Systems Paradigms

    M. Kryszkiewicz;C. Cornelis;D. Ciucci;J. Medina Moreno

  • A selective sampling approach to active feature selection

    Huan Liu;Hiroshi Motoda;Lei Yu

  • Knowledge acquisition for knowledge-based systems

    H. Motoda;R. Mizoguchi;J. Boose;B. Gaines

  • Learning Continuous-Time Information Diffusion Model for Social Behavioral Data Analysis

    Kazumi Saito;Masahiro Kimura;Kouzou Ohara;Hiroshi Motoda

  • Computational Methods of Feature Selection (Chapman & Hall/Crc Data Mining and Knowledge Discovery Series)

    Huan Liu;Hiroshi Motoda

Frequent Co-Authors

Huan Liu
Huan Liu Arizona State University
Longbing Cao
Longbing Cao University of Technology Sydney
Shusaku Tsumoto
Shusaku Tsumoto Shimane University
Guandong Xu
Guandong Xu University of Technology Sydney
Osmar R. Zaïane
Osmar R. Zaïane University of Alberta
Jaideep Srivastava
Jaideep Srivastava University of Minnesota
Riichiro Mizoguchi
Riichiro Mizoguchi Japan Advanced Institute of Science and Technology
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Vincent S. Tseng
Vincent S. Tseng National Yang Ming Chiao Tung University
Nada Lavrač
Nada Lavrač Jozef Stefan Institute

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