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Computer Science
New Zealand
2026

D-Index & Metrics

Computer Science

D-Index
65
Citations
140917
World Ranking
2373
National Ranking
4

Eibe Frank 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 Eibe Frank 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: 170 publications — 35th percentile

35% of scientists in this discipline score the same or lower.

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

Eibe Frank 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 Eibe Frank 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: 65 D-Index — 83rd percentile

83% 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 New Zealand Leader Award
  • 2025 - Research.com Computer Science in New Zealand Leader Award
  • 2023 - Research.com Computer Science in New Zealand Leader Award
  • 2022 - Research.com Computer Science in New Zealand Leader Award

Overview

Eibe Frank is a researcher affiliated with the University of Waikato in New Zealand, specializing primarily in Computer Science with a focus on Artificial Intelligence. Their research spans multiple subfields including Computer Vision and Pattern Recognition, Endocrinology, Diabetes and Metabolism, Rehabilitation, and Periodontics.

The main topics covered in their work include Machine Learning and Data Classification, Domain Adaptation and Few-Shot Learning, Diabetic Foot Ulcer Assessment and Management, Adversarial Robustness in Machine Learning, Explainable Artificial Intelligence (XAI), Data Stream Mining Techniques, and Machine Learning and Algorithms.

Recent papers authored or co-authored by Eibe Frank are:

  • Deep Learning in Diabetic Foot Ulcers Detection: A Comprehensive Evaluation (2020, arXiv (Cornell University))
  • Regularisation of neural networks by enforcing Lipschitz continuity (2020, Machine Learning)
  • The DFUC 2020 Dataset: Analysis Towards Diabetic Foot Ulcer Detection (2021, touchREVIEWS in Endocrinology)
  • GPUTreeShap: massively parallel exact calculation of SHAP scores for tree ensembles (2022, PeerJ Computer Science)
  • Methods for Eliciting Informative Prior Distributions: A Critical Review (2022, Decision Analysis)

Eibe Frank frequently collaborates with several researchers including Bernhard Pfahringer, Geoffrey Holmes, Ian H. Witten, Christopher Pal, and James R. Foulds. Their collaborations have contributed to multiple publications distributed across several venues.

The most common publication venues for Eibe Frank are:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Machine Learning
  • Journal of the Royal Society of New Zealand
  • SSRN Electronic Journal

Best Publications

  • Data mining: practical machine learning tools and techniques with Java implementations

    Ian H. Witten;Eibe Frank

  • Data Mining: Practical Machine Learning Tools and Techniques

    Ian H. Witten;Eibe Frank;Mark A. Hall

  • The WEKA data mining software: an update

    Mark Hall;Eibe Frank;Geoffrey Holmes;Bernhard Pfahringer

  • Classifier chains for multi-label classification

    Jesse Read;Bernhard Pfahringer;Geoff Holmes;Eibe Frank

  • Generating Accurate Rule Sets Without Global Optimization

    Eibe Frank;Ian H. Witten

  • Logistic Model Trees

    Niels Landwehr;Mark Hall;Eibe Frank

  • Logistic model trees

    Niels Landwehr;Mark Hall;Eibe Frank

  • KEA: practical automatic keyphrase extraction

    Ian H. Witten;Gordon W. Paynter;Eibe Frank;Carl Gutwin

  • Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)

    Ian H. Witten;Eibe Frank

  • Data mining in bioinformatics using Weka

    Eibe Frank;Mark Hall;Len Trigg;Geoffrey Holmes

  • Classifier Chains for Multi-label Classification

    Jesse Read;Bernhard Pfahringer;Geoff Holmes;Eibe Frank

  • Domain-specific keyphrase extraction

    Eibe Frank;Gordon W. Paynter;Ian H. Witten;Carl Gutwin

  • Weka: Practical machine learning tools and techniques with Java implementations

    Ian H. Witten;Eibe Frank;Leonard E. Trigg;Mark A. Hall

  • Sentiment knowledge discovery in twitter streaming data

    Albert Bifet;Eibe Frank

  • Weka-A Machine Learning Workbench for Data Mining

    Eibe Frank;Mark A. Hall;Geoffrey Holmes;Richard Kirkby

  • A Simple Approach to Ordinal Classification

    Eibe Frank;Mark Hall

  • Multinomial naive bayes for text categorization revisited

    Ashraf M. Kibriya;Eibe Frank;Bernhard Pfahringer;Geoffrey Holmes

  • Using Model Trees for Classification

    Eibe Frank;Yong Wang;Stuart Inglis;Geoffrey Holmes

  • Gene selection from microarray data for cancer classification-a machine learning approach

    Yu Wang;Igor V. Tetko;Mark A. Hall;Eibe Frank

  • Evaluating the replicability of significance tests for comparing learning algorithms

    Remco R. Bouckaert;Eibe Frank

  • Regularisation of neural networks by enforcing Lipschitz continuity

    Henry Gouk;Eibe Frank;Bernhard Pfahringer;Michael J. Cree

Frequent Co-Authors

Bernhard Pfahringer
Bernhard Pfahringer University of Waikato
Ian H. Witten
Ian H. Witten University of Waikato
Geoffrey Holmes
Geoffrey Holmes University of Waikato
Stefan Kramer
Stefan Kramer Johannes Gutenberg University of Mainz
Chris Pal
Chris Pal Polytechnique Montréal
Remco R. Bouckaert
Remco R. Bouckaert University of Auckland
Albert Bifet
Albert Bifet University of Waikato
Carl Gutwin
Carl Gutwin University of Saskatchewan
Jesse Read
Jesse Read École Polytechnique
Saif M. Mohammad
Saif M. Mohammad National Research Council Canada

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