World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
51
Citations
20017
World Ranking
5208
National Ranking
242

Zeynep Akata 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 Zeynep Akata 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: 142 publications — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Zeynep Akata 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 Zeynep Akata 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: 51 D-Index — 63rd percentile

63% of scientists in this discipline score the same or lower.

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

Overview

Zeynep Akata is affiliated with the University of Tübingen in Germany. Their research primarily falls within the field of Computer Science, with a strong focus on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Signal Processing, and Molecular Biology.

The scientist's work covers a range of topics that include:

  • Domain Adaptation and Few-Shot Learning
  • Multimodal Machine Learning Applications
  • Advanced Neural Network Applications
  • Advanced Image and Video Retrieval Techniques
  • Topic Modeling
  • COVID-19 diagnosis using AI
  • Explainable Artificial Intelligence (XAI)

Among the notable recent papers authored by Zeynep Akata are:

  • Computer Vision and Pattern Recognition 2020, 2021, published in International Journal of Computer Vision
  • A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence, 2020, published in Computer

The scientist also contributed to several other works including surveys and studies on semi-supervised and unsupervised deep learning, learning robust representations, and graph embeddings for zero-shot learning, published mainly in venues like IEEE Transactions on Pattern Analysis and Machine Intelligence and arXiv.

Zeynep Akata frequently publishes in the following venues:

  • arXiv (Cornell University)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  • Lecture notes in computer science

Collaboration is a significant aspect of the scientist's research, as indicated by frequent co-authors such as Massimiliano Mancini, A. Sophia Koepke, Karsten Roth, Yongqin Xian, and Stephan Alaniz.

In addition to articles, the scientist has published a book titled Pattern Recognition in 2021 through Springer Science+Business Media.

Best Publications

  • Generative adversarial text to image synthesis

    Scott Reed;Zeynep Akata;Xinchen Yan;Lajanugen Logeswaran

  • Zero-Shot Learning—A Comprehensive Evaluation of the Good, the Bad and the Ugly

    Yongqin Xian;Christoph H. Lampert;Bernt Schiele;Zeynep Akata

  • Evaluation of output embeddings for fine-grained image classification

    Zeynep Akata;Scott Reed;Daniel Walter;Honglak Lee

  • Feature Generating Networks for Zero-Shot Learning

    Yongqin Xian;Tobias Lorenz;Bernt Schiele;Zeynep Akata

  • Learning Deep Representations of Fine-Grained Visual Descriptions

    Scott Reed;Zeynep Akata;Honglak Lee;Bernt Schiele

  • Label-Embedding for Image Classification

    Zeynep Akata;Florent Perronnin;Zaid Harchaoui;Cordelia Schmid

  • Zero-Shot Learning — The Good, the Bad and the Ugly

    Yongqin Xian;Bernt Schiele;Zeynep Akata

  • Label-Embedding for Attribute-Based Classification

    Zeynep Akata;Florent Perronnin;Zaid Harchaoui;Cordelia Schmid

  • Latent Embeddings for Zero-Shot Classification

    Yongqin Xian;Zeynep Akata;Gaurav Sharma;Quynh Nguyen

  • Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders

    Edgar Schonfeld;Sayna Ebrahimi;Samarth Sinha;Trevor Darrell

  • Generating Visual Explanations

    Lisa Anne Hendricks;Zeynep Akata;Marcus Rohrbach;Marcus Rohrbach;Jeff Donahue

  • F-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning

    Yongqin Xian;Saurabh Sharma;Bernt Schiele;Zeynep Akata

  • Learning what and where to draw

    Scott Reed;Zeynep Akata;Santosh Mohan;Samuel Tenka

  • Multimodal Explanations: Justifying Decisions and Pointing to the Evidence

    Dong Huk Park;Lisa Anne Hendricks;Zeynep Akata;Anna Rohrbach

  • A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence

    Zeynep Akata;Dan Balliet;Maarten de Rijke;Frank Dignum

  • Textual Explanations for Self-Driving Vehicles

    Jinkyu Kim;Anna Rohrbach;Trevor Darrell;John F. Canny

  • Explainable AI: The new 42?

    Randy Goebel;Ajay Chander;Katharina Holzinger;Freddy Lecue

  • Computer Vision and Pattern Recognition 2020

    Zeynep Akata;Andreas Geiger;Torsten Sattler

  • Learning Deep Representations of Fine-grained Visual Descriptions

    Scott Reed;Zeynep Akata;Bernt Schiele;Honglak Lee

  • Exploiting Saliency for Object Segmentation from Image Level Labels

    Seong Joon Oh;Rodrigo Benenson;Anna Khoreva;Zeynep Akata

  • Learning Robust Representations via Multi-View Information Bottleneck

    Marco Federici;Anjan Dutta;Patrick Forré;Nate Kushman

  • Zero-Shot Learning with Structured Embeddings

    Zeynep Akata;Honglak Lee;Bernt Schiele

Frequent Co-Authors

Bernt Schiele
Bernt Schiele Max Planck Institute for Informatics
Trevor Darrell
Trevor Darrell University of California, Berkeley
Cordelia Schmid
Cordelia Schmid French Institute for Research in Computer Science and Automation - INRIA
Honglak Lee
Honglak Lee University of Michigan–Ann Arbor
Barbara Caputo
Barbara Caputo Polytechnic University of Turin
Marcus Rohrbach
Marcus Rohrbach Facebook (United States)
Max Welling
Max Welling University of Amsterdam
Anna Rohrbach
Anna Rohrbach Technical University of Darmstadt
Zaid Harchaoui
Zaid Harchaoui University of Washington

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

Expanding your education in Computer Science opens doors to many promising career paths. Many students start by exploring the best majors in college that relate to technology and computer science. Choosing the right major is crucial, as it can set the foundation for specialized roles in software engineering, AI, cybersecurity, and more.

After your undergraduate degree, you may consider pursuing graduate studies. If you want a flexible path, some of the easy masters degrees can help you quickly build advanced skills without an overwhelming workload. This can be a smart choice for professionals balancing work and study.

Ambitious students sometimes aim for terminal degrees. With the rise of distance learning, there are now most affordable online doctoral programs available that offer flexibility and cost savings. Additionally, educators and administrators can look into edd online programs that provide a fast-track route to leadership roles in academic or education technology fields.

Best Scientists Citing Zeynep Akata

Trending Scientists

Recently Published Articles