World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
16777
World Ranking
7379
National Ranking
123

Ran El-Yaniv 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 Ran El-Yaniv 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: 124 publications — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Ran El-Yaniv 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 Ran El-Yaniv 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: 44 D-Index — 48th percentile

48% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Ran El-Yaniv is affiliated with Technion - Israel Institute of Technology in Israel. Their research primarily spans the field of Computer Science, with a focus on several subfields and topics related to artificial intelligence and machine learning.

The main areas of study include:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Radiology, Nuclear Medicine and Imaging
  • Signal Processing
  • Cognitive Neuroscience

Key research topics addressed by Ran El-Yaniv encompass:

  • Adversarial Robustness in Machine Learning
  • Anomaly Detection Techniques and Applications
  • COVID-19 diagnosis using AI
  • Machine Learning and Data Classification
  • Advanced Neural Network Applications
  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning

Ran El-Yaniv has published extensively, with frequent contributions to arXiv (Cornell University) and other venues such as Zenodo (CERN European Organization for Nuclear Research) and Acta Ophthalmologica. Prominent recent papers include:

  • HydroNets: Leveraging River Structure for Hydrologic Modeling, 2020, arXiv (Cornell University)
  • DNF-Net: A Neural Architecture for Tabular Data, 2020, arXiv (Cornell University)
  • BebopNet: Deep neural models for personalized jazz improvisations, 2020, Zenodo (CERN European Organization for Nuclear Research)
  • Disrupting Deep Uncertainty Estimation Without Harming Accuracy, 2021, arXiv (Cornell University)
  • Train on Small, Play the Large: Scaling Up Board Games with AlphaZero and GNN, 2021, arXiv (Cornell University)

Collaborations are a consistent element of their work, with frequent co-authors including Ido Galil, Mohammed Dabbah, Zach Moshe, Guy Bar-Shalom, and Gal Elidan.

Best Publications

  • Online Computation and Competitive Analysis

    Allan Borodin;Ran El-Yaniv

  • Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

    Matthieu Courbariaux;Itay Hubara;Daniel Soudry;Ran El-Yaniv

  • Quantized neural networks: training neural networks with low precision weights and activations

    Itay Hubara;Matthieu Courbariaux;Daniel Soudry;Ran El-Yaniv

  • Binarized Neural Networks

    Itay Hubara;Matthieu Courbariaux;Daniel Soudry;Ran El-Yaniv

  • On prediction using variable order Markov models

    Ron Begleiter;Ran El-Yaniv;Golan Yona

  • Online Choice of Active Learning Algorithms

    Yoram Baram;Ran El-Yaniv;Kobi Luz

  • Distributional word clusters vs. words for text categorization

    Ron Bekkerman;Ran El-Yaniv;Naftali Tishby;Yoad Winter

  • Deep Anomaly Detection Using Geometric Transformations

    Izhak Golan;Ran El-Yaniv

  • Texture mixing and texture movie synthesis using statistical learning

    Z. Bar-Joseph;R. El-Yaniv;D. Lischinski;M. Werman

  • Selective Classification for Deep Neural Networks

    Yonatan Geifman;Ran El-Yaniv

  • Can We Learn to Beat the Best Stock

    A. Borodin;R. El-Yaniv;V. Gogan

  • Optimal Search and One-Way Trading Online Algorithms

    Ran El-Yaniv;Amos Fiat;Richard M. Karp;G. Turpin

  • On the Foundations of Noise-free Selective Classification

    Ran El-Yaniv;Yair Wiener

  • On feature distributional clustering for text categorization

    Ron Bekkerman;Ran El-Yaniv;Naftali Tishby;Yoad Winter

  • Methods and systems of supervised learning of semantic relatedness

    Ran El-Yaniv;David Yanay

  • SelectiveNet: A Deep Neural Network with an Integrated Reject Option

    Yonatan Geifman;Ran El-Yaniv

  • Multi-way distributional clustering via pairwise interactions

    Ron Bekkerman;Ran El-Yaniv;Andrew McCallum

  • Competitive analysis of financial games

    R. El-Yaniv;A. Fiat;R. Karp;G. Turpin

  • Learn on Source, Refine on Target: A Model Transfer Learning Framework with Random Forests

    Noam Segev;Maayan Harel;Shie Mannor;Koby Crammer

  • Competitive Optimal On-Line Leasing

    Ran El-Yaniv;Ron Kaniel;Nathan Linial

  • Deep Active Learning over the Long Tail.

    Yonatan Geifman;Ran El-Yaniv

Frequent Co-Authors

Allan Borodin
Allan Borodin University of Toronto
Ron Meir
Ron Meir Technion – Israel Institute of Technology
Shlomo Dubnov
Shlomo Dubnov University of California, San Diego
Daniel Soudry
Daniel Soudry Technion – Israel Institute of Technology
Yoshua Bengio
Yoshua Bengio University of Montreal
Ziv Bar-Joseph
Ziv Bar-Joseph Carnegie Mellon University
Naftali Tishby
Naftali Tishby Hebrew University of Jerusalem
Michael Werman
Michael Werman Hebrew University of Jerusalem
Richard M. Karp
Richard M. Karp University of California, Berkeley
Dani Lischinski
Dani Lischinski Hebrew University of Jerusalem

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Whether you’re starting your studies or seeking advanced credentials in computer science, there are a range of online degree options to consider. Many students seek the cheapest online bachelors degree programs to minimize student debt and make higher education more accessible.

For those interested in specialized technology fields, it’s important to explore the true online engineering degree cost. Understanding tuition and additional fees is crucial for effective financial planning.

Professionals looking to advance into leadership roles may consider pursuing online executive mba programs. These flexible options allow you to balance career development with your current job responsibilities.

Additionally, interdisciplinary paths—such as library and information science—are increasingly relevant as digital resources expand. For those interested in organizing and managing digital information, a library science degree offers a unique career trajectory that complements computer science skills.

Best Scientists Citing Ran El-Yaniv

Trending Scientists

Recently Published Articles