World's Best Scientists 2026 revealed!
Geoffrey I. Webb

Geoffrey I. Webb

Award Badge
Computer Science
Australia
2025

D-Index & Metrics

Computer Science

D-Index
78
Citations
30445
World Ranking
1177
National Ranking
26

Geoffrey I. Webb 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 Geoffrey I. Webb 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: 340 publications — 80th percentile

80% of scientists in this discipline score the same or lower.

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

Geoffrey I. Webb 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 Geoffrey I. Webb 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

  • 2025 - Research.com Computer Science in Australia Leader Award
  • 2023 - Research.com Computer Science in Australia Leader Award
  • 2022 - Research.com Computer Science in Australia Leader Award

Overview

Geoffrey I. Webb is affiliated with Monash University in Australia. Their academic work primarily spans the field of Computer Science with 253 publications.

Their research covers several subfields, including:

  • Artificial Intelligence
  • Signal Processing
  • Molecular Biology
  • Electrical and Electronic Engineering
  • Information Systems

The main topics of their research output involve:

  • Time Series Analysis and Forecasting
  • Anomaly Detection Techniques and Applications
  • Machine Learning in Bioinformatics
  • Energy Load and Power Forecasting
  • Smart Grid Energy Management
  • Music and Audio Processing
  • Web Data Mining and Analysis

Geoffrey I. Webb has frequently published in a variety of venues, notably:

  • Zenodo (CERN European Organization for Nuclear Research)
  • OPAL (Open@LaTrobe) (La Trobe University)
  • arXiv (Cornell University)
  • Data Mining and Knowledge Discovery
  • Briefings in Bioinformatics

They have collaborated extensively with several researchers, with frequent co-authors including:

  • Christoph Bergmeir
  • Rakshitha Godahewa
  • Pablo Montero-Manso
  • Rob J. Hyndman
  • Chang Wei Tan

Recent publications provide insight into the scope of their research interests. These include:

  • iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization, 2021, Nucleic Acids Research
  • A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection, 2024, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Deep Learning for Time Series Anomaly Detection: A Survey, 2024, ACM Computing Surveys
  • MultiRocket: multiple pooling operators and transformations for fast and effective time series classification, 2022, Data Mining and Knowledge Discovery
  • Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey, 2024, ACM Computing Surveys

Geoffrey I. Webb has authored books published by Springer Science+Business Media, such as Advances in Knowledge Discovery and Data Mining (2022).

Best Publications

  • Encyclopedia of Machine Learning

    Claude Sammut;Geoffrey I. Webb

  • InceptionTime: Finding AlexNet for time series classification

    Hassan Ismail Fawaz;Benjamin Lucas;Germain Forestier;Germain Forestier;Charlotte Pelletier;Charlotte Pelletier

  • ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels

    Angus Dempster;François Petitjean;Geoffrey I. Webb

  • Not so naive Bayes: aggregating one-dependence estimators

    Geoffrey I. Webb;Janice R. Boughton;Zhihai Wang

  • MultiBoosting: A Technique for Combining Boosting and Wagging

    Geoffrey I. Webb

  • Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

    Longbing Cao;Chengqi Zhang;Thorsten Joachims;Geoff Webb

  • iFeature: a Python package and web server for features extraction and selection from protein and peptide sequences.

    Zhen Chen;Pei Zhao;Fuyi Li;André Leier

  • MiniRocket: A Very Fast (Almost) Deterministic Transform for Time Series Classification

    Angus Dempster;Daniel F. Schmidt;Geoffrey I. Webb

  • Machine Learning for User Modeling

    Geoffrey I. Webb;Michael J. Pazzani;Daniel Billsus

  • Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series

    Charlotte Pelletier;Geoffrey I. Webb;François Petitjean

  • Characterizing concept drift

    Geoffrey I. Webb;Roy Hyde;Hong Cao;Hai Long Nguyen

  • Supervised Descriptive Rule Discovery: A Unifying Survey of Contrast Set, Emerging Pattern and Subgroup Mining

    Petra Kralj Novak;Nada Lavrač;Geoffrey I. Webb

  • iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data.

    Zhen Chen;Pei Zhao;Fuyi Li;Tatiana T Marquez-Lago

  • A novel selective naïve Bayes algorithm

    Shenglei Chen;Geoffrey I. Webb;Linyuan Liu;Xin Ma

  • Lazy Learning of Bayesian Rules

    Zijian Zheng;Geoffrey I. Webb

  • Encyclopedia of Machine Learning and Data Mining

    Claude Sammut;Geoffrey I. Webb

  • Multistrategy ensemble learning: reducing error by combining ensemble learning techniques

    G.I. Webb;Z. Zheng

  • Discovering significant patterns

    Geoffrey I. Webb

  • TS-CHIEF: a scalable and accurate forest algorithm for time series classification

    Ahmed Shifaz;Charlotte Pelletier;Charlotte Pelletier;François Petitjean;Geoffrey I. Webb

  • Discretization for naive-Bayes learning: managing discretization bias and variance

    Ying Yang;Geoffrey I. Webb

  • OPUS: an efficient admissible algorithm for unordered search

    Geoffrey I. Webb

  • Dynamic Time Warping Averaging of Time Series Allows Faster and More Accurate Classification

    Francois Petitjean;Germain Forestier;Geoffrey I. Webb;Ann E. Nicholson

Frequent Co-Authors

Jiangning Song
Jiangning Song Monash University
Tatsuya Akutsu
Tatsuya Akutsu Kyoto University
André Leier
André Leier University of Alabama at Birmingham
Kuo-Chen Chou
Kuo-Chen Chou The Gordon Life Science Institute
Kai Ming Ting
Kai Ming Ting Nanjing University
James C. Whisstock
James C. Whisstock Monash University
Trevor Lithgow
Trevor Lithgow Monash University
Robert N. Pike
Robert N. Pike La Trobe University
Bart Goethals
Bart Goethals University of Antwerp
Chengqi Zhang
Chengqi Zhang Hong Kong Polytechnic University

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