World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
56
Citations
33371
World Ranking
3936
National Ranking
1869

Charles Elkan 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 Charles Elkan 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: 132 publications — 19th percentile

19% of scientists in this discipline score the same or lower.

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

Charles Elkan 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 Charles Elkan 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: 56 D-Index — 72nd percentile

72% 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

  • 1996 - Hellman Fellow

Overview

Charles Elkan is affiliated with the University of California, San Diego in the United States. Their research spans multiple areas within computer science, with a focus on the development and application of machine learning techniques in remote sensing and educational technologies.

Elkan's recent scholarly contributions include the paper One-Class Remote Sensing Classification From Positive and Unlabeled Background Data published in 2020 in the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. Another recent work titled Gamified crowd-sourcing of high-quality data for visual fine-tuning appeared in 2024 on arXiv (Cornell University).

Their research topics cover a range of specialized and interdisciplinary fields. These include:

  • Remote-Sensing Image Classification
  • Remote Sensing in Agriculture
  • Machine Learning and Data Classification
  • Data Visualization and Analytics
  • Educational Games and Gamification
  • Virtual Reality Applications and Impacts

Elkan is active in several subfields of computer science:

  • Media Technology
  • Ecology
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Developmental and Educational Psychology

They have collaborated regularly with co-authors including Wenkai Li, Qinghua Guo, Shashank Yadav, Rachana Tomar, and Gourav Jain.

Elkan's work has been published in venues such as:

  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • arXiv (Cornell University)

In recognition of their research activities, Charles Elkan received the Hellman Fellowship in 1996.

Best Publications

  • Fitting a mixture model by expectation maximization to discover motifs in biopolymers.

    Timothy L. Bailey;Charles Elkan

  • The foundations of cost-sensitive learning

    Charles Elkan

  • A Critical Review of Recurrent Neural Networks for Sequence Learning

    Zachary C. Lipton;John Berkowitz;Charles Elkan

  • Transforming classifier scores into accurate multiclass probability estimates

    Bianca Zadrozny;Charles Elkan

  • Learning classifiers from only positive and unlabeled data

    Charles Elkan;Keith Noto

  • Learning to Diagnose with LSTM Recurrent Neural Networks

    Zachary C. Lipton;David C. Kale;Charles Elkan;Randall Wetzell

  • Learning the k in k-means

    Greg Hamerly;Charles Elkan

  • Using the triangle inequality to accelerate k-means

    Charles Elkan

  • The Transporter Classification Database: recent advances

    Milton H. Saier;Ming Ren Yen;Keith Noto;Dorjee G. Tamang

  • Unsupervised Learning of Multiple Motifs in Biopolymers Using Expectation Maximization

    Timothy L. Bailey;Charles Elkan

  • The value of prior knowledge in discovering motifs with MEME.

    Timothy L. Bailey;Charles Elkan

  • Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers

    Bianca Zadrozny;Charles Elkan

  • The field matching problem: Algorithms and applications

    Alvaro E. Monge;Charles P. Elkan

  • Alternatives to the k-means algorithm that find better clusterings

    Greg Hamerly;Charles Elkan

  • Learning to Diagnose with LSTM Recurrent Neural Networks

    Zachary C. Lipton;David C. Kale;Charles Elkan;Randall Wetzel

  • Link prediction via matrix factorization

    Aditya Krishna Menon;Charles Elkan

  • Optimal thresholding of classifiers to maximize F1 measure

    Zachary C. Lipton;Charles Elkan;Balakrishnan Naryanaswamy

  • Learning and making decisions when costs and probabilities are both unknown

    Bianca Zadrozny;Charles Elkan

  • An Efficient Domain-Independent Algorithm for Detecting Approximately Duplicate Database Records.

    Alvaro E. Monge;Charles Elkan

  • The paradoxical success of fuzzy logic

    C. Elkan;H.R. Berenji;B. Chandrasekaran;C.J.S. de Silva

Frequent Co-Authors

Aditya Krishna Menon
Aditya Krishna Menon Google (United States)
Timothy L. Bailey
Timothy L. Bailey University of Nevada Reno
Zachary C. Lipton
Zachary C. Lipton Carnegie Mellon University
Michael E. Baker
Michael E. Baker University of California, San Diego
Milton H. Saier
Milton H. Saier University of California, San Diego
Ramón Huerta
Ramón Huerta Autonomous University of Madrid
Qinghua Guo
Qinghua Guo Chinese Academy of Sciences
Padhraic Smyth
Padhraic Smyth University of California, Irvine
Alexander Russell
Alexander Russell University of Connecticut
Domonkos Tikk
Domonkos Tikk Gravity Research & Development Zrt.

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