World's Best Scientists 2026 revealed!
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Computer Science
Japan
2025

D-Index & Metrics

Computer Science

D-Index
46
Citations
10669
World Ranking
6756
National Ranking
97

Kenji Fukumizu 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 Kenji Fukumizu 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: 184 publications — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Kenji Fukumizu 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 Kenji Fukumizu 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: 46 D-Index — 53rd percentile

53% 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

Kenji Fukumizu is affiliated with The Institute of Statistical Mathematics in Japan. Their research primarily focuses on computer science, with a significant emphasis on artificial intelligence, statistics and probability, computer vision and pattern recognition, computational theory and mathematics, and materials chemistry.

The scientist's work covers several main topics, including domain adaptation and few-shot learning, topological and geometric data analysis, statistical methods and inference, machine learning and data classification, generative adversarial networks and image synthesis, Gaussian processes and Bayesian inference, and machine learning applications in materials science.

Fukumizu has published extensively in various venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • npj Computational Materials
  • IEEE Access
  • Pattern Recognition Letters

Co-authorship has been a notable aspect of their work. Frequent collaborators include:

  • Shunya Minami
  • Masanori Koyama
  • Pengzhou Wu
  • Tam Le
  • Truyen Nguyen

Selected recent papers by Kenji Fukumizu include:

  • "Smoothness and Stability in GANs," 2020, arXiv (Cornell University)
  • "ALGAN: Anomaly Detection by Generating Pseudo Anomalous Data via Latent Variables," 2022, IEEE Access
  • "Advantage of Deep Neural Networks for Estimating Functions with Singularity on Hypersurfaces," 2020, arXiv (Cornell University)
  • "Causal Mosaic: Cause-Effect Inference via Nonlinear ICA and Ensemble Method," 2020, arXiv (Cornell University)
  • "Meta Learning for Causal Direction," 2021, Proceedings of the AAAI Conference on Artificial Intelligence

Best Publications

  • A Kernel Statistical Test of Independence

    Arthur Gretton;Kenji Fukumizu;Choon H. Teo;Le Song

  • Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces

    Kenji Fukumizu;Francis R. Bach;Michael I. Jordan

  • Hilbert Space Embeddings and Metrics on Probability Measures

    Bharath K. Sriperumbudur;Arthur Gretton;Kenji Fukumizu;Bernhard Schölkopf

  • Kernel Mean Embedding of Distributions: A Review and Beyond

    Krikamol Muandet;Kenji Fukumizu;Bharath K. Sriperumbudur;Bernhard Schölkopf

  • Optimal kernel choice for large-scale two-sample tests

    Arthur Gretton;Dino Sejdinovic;Heiko Strathmann;Sivaraman Balakrishnan

  • Kernel Measures of Conditional Dependence

    Kenji Fukumizu;Arthur Gretton;Xiaohai Sun;Bernhard Schölkopf

  • Universality, Characteristic Kernels and RKHS Embedding of Measures

    Bharath K. Sriperumbudur;Kenji Fukumizu;Gert R. G. Lanckriet

  • Hilbert space embeddings of conditional distributions with applications to dynamical systems

    Le Song;Jonathan Huang;Alex Smola;Kenji Fukumizu

  • Statistical Consistency of Kernel Canonical Correlation Analysis

    Kenji Fukumizu;Francis R. Bach;Arthur Gretton

  • On the empirical estimation of integral probability metrics

    Bharath K. Sriperumbudur;Kenji Fukumizu;Arthur Gretton;Bernhard Schoelkopf

  • Adaptive Method of Realizing Natural Gradient Learning for Multilayer Perceptrons

    Shun-Ichi Amari;Hyeyoung Park;Kenji Fukumizu

  • Kernel Embeddings of Conditional Distributions: A Unified Kernel Framework for Nonparametric Inference in Graphical Models

    Le Song;K. Fukumizu;A. Gretton

  • Local minima and plateaus in hierarchical structures of multilayer perceptions

    K. Fukumizu;S. Amari

  • A Fast, Consistent Kernel Two-Sample Test

    Arthur Gretton;Kenji Fukumizu;Zaïd Harchaoui;Bharath K. Sriperumbudur

  • Adaptive natural gradient learning algorithms for various stochastic models

    H. Park;S.-I. Amari;K. Fukumizu

  • Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions

    Kenji Fukumizu;Arthur Gretton;Gert R. Lanckriet;Bernhard Schölkopf

  • Injective hilbert space embeddings of probability measures

    Bharath K. Sriperumbudur;Arthur Gretton;Kenji Fukumizu;Gert R. G. Lanckriet

  • Learning from Distributions via Support Measure Machines

    Krikamol Muandet;Kenji Fukumizu;Francesco Dinuzzo;Bernhard Schölkopf

  • Persistence weighted Gaussian kernel for topological data analysis

    Genki Kusano;Kenji Fukumizu;Yasuaki Hiraoka

  • Kernel Bayes' rule: Bayesian inference with positive definite kernels

    Kenji Fukumizu;Le Song;Arthur Gretton

  • On integral probability metrics, φ-divergences and binary classification

    Bharath K. Sriperumbudur;Kenji Fukumizu;Arthur Gretton;Bernhard Schölkopf

  • Density Estimation in Infinite Dimensional Exponential Families

    Bharath K. Sriperumbudur;Kenji Fukumizu;Arthur Gretton;Aapo Hyvärinen

Frequent Co-Authors

Arthur Gretton
Arthur Gretton University College London
Bernhard Schölkopf
Bernhard Schölkopf Max Planck Institute for Intelligent Systems
Taiji Suzuki
Taiji Suzuki University of Tokyo
Gert R. G. Lanckriet
Gert R. G. Lanckriet University of California, San Diego
Francis Bach
Francis Bach École Normale Supérieure
Le Song
Le Song Mohamed bin Zayed University of Artificial Intelligence
Shun-ichi Amari
Shun-ichi Amari RIKEN Center for Brain Science
Alexander J. Smola
Alexander J. Smola Amazon (United States)
Marco Cuturi
Marco Cuturi École Nationale de la Statistique et de l'Administration Économique

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