World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
56
Citations
20100
World Ranking
3965
National Ranking
150

Shai Ben-David 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 Shai Ben-David 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: 169 publications — 34th percentile

34% of scientists in this discipline score the same or lower.

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

Shai Ben-David 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 Shai Ben-David 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.

Overview

Shai Ben-David is affiliated with the University of Waterloo in Canada and specializes in the field of Computer Science. Their research covers a range of subfields including Artificial Intelligence, Computational Theory and Mathematics, Signal Processing, Control and Systems Engineering, and Statistical and Nonlinear Physics.

Their work primarily focuses on topics such as Machine Learning and Algorithms, Advanced Clustering Algorithms Research, Data Management and Algorithms, Machine Learning and Data Classification, Adversarial Robustness in Machine Learning, Privacy-Preserving Technologies in Data, and Rough Sets and Fuzzy Logic.

Ben-David has published extensively in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Pattern Recognition
  • Journal of the ACM
  • Proceedings of the AAAI/ACM Conference on AI Ethics and Society

Their recent papers include:

  • "Weighted Clustering" (2021), Proceedings of the AAAI Conference on Artificial Intelligence
  • "Enforcing Interpretability and its Statistical Impacts: Trade-offs between Accuracy and Interpretability" (2020), arXiv (Cornell University)
  • "Weighted clustering: Towards solving the user's dilemma" (2021), Pattern Recognition
  • "Near-optimal Sample Complexity Bounds for Robust Learning of Gaussian Mixtures via Compression Schemes" (2020), Journal of the ACM
  • "Continual Learning: Applications and the Road Forward" (2023), arXiv (Cornell University)

Frequent collaborators include Tosca Lechner, Margareta Ackerman, Simina Brânzei, David Loker, and Alex Bie. Ben-David has coauthored multiple works with these researchers, with the highest number of collaborations recorded with Tosca Lechner.

Best Publications

  • Understanding Machine Learning: From Theory To Algorithms

    Shai Shalev-Shwartz;Shai Ben-David

  • A theory of learning from different domains

    Shai Ben-David;John Blitzer;Koby Crammer;Alex Kulesza

  • Analysis of Representations for Domain Adaptation

    Shai Ben-David;John Blitzer;Koby Crammer;Fernando Pereira

  • Detecting change in data streams

    Daniel Kifer;Shai Ben-David;Johannes Gehrke

  • On the power of randomization in on-line algorithms

    S. Ben-David;A. Borodin;R. Karp;G. Tardos

  • Scale-sensitive dimensions, uniform convergence, and learnability

    Noga Alon;Shai Ben-David;Nicolò Cesa-Bianchi;David Haussler

  • Exploiting Task Relatedness for Multiple Task Learning

    Shai Ben-David;Shai Ben-David;Reba Schuller

  • On the theory of average case complexity

    Shai Ben-David;Benny Chor;Oded Goldreich;Michael Luby

  • A sober look at clustering stability

    Shai Ben-David;Ulrike von Luxburg;Dávid Pál

  • On the power of randomization in online algorithms

    S. Ben-David;A. Borodin;R. Karp;G. Tardos

  • Impossibility Theorems for Domain Adaptation

    Shai Ben-David;Tyler Lu;Teresa Luu;Dávid Pál

  • Measures of Clustering Quality: A Working Set of Axioms for Clustering

    Shai Ben-David;Margareta Ackerman

  • Empirical Risk Minimization Under Fairness Constraints

    Michele Donini;Luca Oneto;Shai Ben-David;John S. Shawe-Taylor

  • On the difficulty of approximately maximizing agreements

    Shai Ben-David;Nadav Eiron;Philip M. Long

  • A new measure for the study of on-line algorithms

    Shai Ben-David;Allan Borodin

  • Clusterability: A Theoretical Study

    Margareta Ackerman;Shai Ben-David

  • Characterizations of Learnability for Classes of {0, ..., n)-Valued Functions

    S. Bendavid;N. Cesabianchi;D. Haussler;P.M. Long

  • A uniqueness theorem for clustering

    Reza Bosagh Zadeh;Shai Ben-David

  • Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning.

    Shai Ben-David;Tyler Lu;Dávid Pál

  • Agnostic Online Learning.

    Shai Ben-David;Dávid Pál;Shai Shalev-Shwartz

  • On the Power of Randomization in Online Algorithms (Extended Abstract)

    Shai Ben-David;Allan Borodin;Richard M. Karp;Gábor Tardos

Frequent Co-Authors

Shai Shalev-Shwartz
Shai Shalev-Shwartz Hebrew University of Jerusalem
Eyal Kushilevitz
Eyal Kushilevitz Technion – Israel Institute of Technology
Michael Lindenbaum
Michael Lindenbaum Technion – Israel Institute of Technology
Yishay Mansour
Yishay Mansour Tel Aviv University
Ihab F. Ilyas
Ihab F. Ilyas University of Waterloo
Oded Goldreich
Oded Goldreich Weizmann Institute of Science
Benny Chor
Benny Chor Tel Aviv University
Peter L. Bartlett
Peter L. Bartlett University of California, Berkeley
Nicolò Cesa-Bianchi
Nicolò Cesa-Bianchi University of Milan
Philip M. Long
Philip M. Long Google (United States)

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