World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
46
Citations
24201
World Ranking
6634
National Ranking
395

Yarin Gal 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 Yarin Gal 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: 164 publications — 32nd percentile

32% of scientists in this discipline score the same or lower.

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

Yarin Gal 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 Yarin Gal 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: 46 D-Index — 53rd percentile

53% of scientists in this discipline score the same or lower.

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

Overview

Yarin Gal is affiliated with the University of Oxford in the United Kingdom and has a significant body of research in the field of Computer Science. Their work primarily focuses on Artificial Intelligence, contributing extensively to subfields such as Computer Vision and Pattern Recognition, Molecular Biology, Global and Planetary Change, and Infectious Diseases.

Their research interest spans several topics, including:

  • Machine Learning and Algorithms
  • Machine Learning and Data Classification
  • Adversarial Robustness in Machine Learning
  • Topic Modeling
  • Domain Adaptation and Few-Shot Learning
  • Gaussian Processes and Bayesian Inference
  • Explainable Artificial Intelligence (XAI)

Yarin Gal has published a considerable number of papers, many of which have appeared in high-impact venues. Frequent publication venues include:

  • arXiv (Cornell University) with 126 publications
  • bioRxiv (Cold Spring Harbor Laboratory) with 10 publications
  • Nature with 7 publications
  • Zenodo (CERN European Organization for Nuclear Research) with 3 publications
  • Nature Communications with 2 publications

Some of the recent papers from their work include:

  • Inferring the effectiveness of government interventions against COVID-19, 2020, Science
  • Disease variant prediction with deep generative models of evolutionary data, 2021, Nature
  • AI models collapse when trained on recursively generated data, 2024, Nature
  • Detecting hallucinations in large language models using semantic entropy, 2024, Nature
  • Uncertainty Estimation Using a Single Deep Deterministic Neural Network, 2020, arXiv (Cornell University)

Frequent collaborators in Yarin Gal's research include:

  • Sören Mindermann
  • Pascal Notin
  • Andrew Jesson
  • Andreas Kirsch
  • Jan Brauner

Best Publications

  • Dropout as a Bayesian approximation: representing model uncertainty in deep learning

    Yarin Gal;Zoubin Ghahramani

  • What uncertainties do we need in Bayesian deep learning for computer vision

    Alex Kendall;Yarin Gal

  • Multi-task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics

    Roberto Cipolla;Yarin Gal;Alex Kendall

  • A theoretically grounded application of dropout in recurrent neural networks

    Yarin Gal;Zoubin Ghahramani

  • Deep Bayesian active learning with image data

    Yarin Gal;Riashat Islam;Zoubin Ghahramani

  • Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference

    Yarin Gal;Zoubin Ghahramani

  • Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics

    Alex Kendall;Yarin Gal;Roberto Cipolla

  • Real Time Image Saliency for Black Box Classifiers

    Piotr Dabkowski;Yarin Gal

  • Concrete Dropout

    Yarin Gal;Jiri Hron;Alex Kendall

  • BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning

    Andreas Kirsch;Joost van Amersfoort;Yarin Gal

  • Uncertainty Estimation Using a Single Deep Deterministic Neural Network

    Joost van Amersfoort;Lewis Smith;Yee Whye Teh;Yarin Gal

  • Towards Robust Evaluations of Continual Learning

    Sebastian Farquhar;Yarin Gal

  • Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning

    Rowan McAllister;Yarin Gal;Alex Kendall;Mark van der Wilk

  • Understanding Measures of Uncertainty for Adversarial Example Detection

    Lewis Smith;Yarin Gal

  • Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval

    Unknown

  • Evaluating Bayesian Deep Learning Methods for Semantic Segmentation

    Jishnu Mukhoti;Yarin Gal

  • Towards global flood mapping onboard low cost satellites with machine learning.

    Gonzalo Mateo-Garcia;Joshua Veitch-Michaelis;Lewis Smith;Silviu Vlad Oprea

  • Dropout inference in Bayesian neural networks with alpha-divergences

    Yingzhen Li;Yarin Gal

  • Learning Invariant Representations for Reinforcement Learning without Reconstruction

    Amy Zhang;Rowan Thomas McAllister;Roberto Calandra;Yarin Gal

  • Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam

    Mohammad Emtiyaz Khan;Didrik Nielsen;Voot Tangkaratt;Wu Lin

  • Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models

    Yarin Gal;Mark van der Wilk;Carl Rasmussen

  • VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

    Luisa Zintgraf;Kyriacos Shiarlis;Maximilian Igl;Sebastian Schulze

  • Can autonomous vehicles identify, recover from, and adapt to distribution shifts?

    Angelos Filos;Panagiotis Tigkas;Rowan McAllister;Nicholas Rhinehart

Frequent Co-Authors

Zoubin Ghahramani
Zoubin Ghahramani University of Cambridge
Yee Whye Teh
Yee Whye Teh University of Oxford
Sergey Levine
Sergey Levine University of California, Berkeley
Samir Bhatt
Samir Bhatt Imperial College London
Marta Kwiatkowska
Marta Kwiatkowska University of Oxford
Joni Dambre
Joni Dambre Ghent University
Arthur Gretton
Arthur Gretton University College London
Roberto Cipolla
Roberto Cipolla University of Cambridge
Guy Schumann
Guy Schumann University of Bristol
Debora S. Marks
Debora S. Marks Harvard University

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

Studying Computer Science in the USA opens doors to a wide range of online education options and career opportunities. Many online colleges that accept 2.0 gpa make technology degrees more accessible to a broader group of students, helping those with diverse academic backgrounds start their journey in IT.

If you want to accelerate your studies, consider enrolling in an accelerated computer science degree. These fast-track programs allow motivated learners to complete their education and enter the workforce sooner.

Expanding your career options can also mean looking at related disciplines. For example, with a strong computer science foundation, you can pursue fields like environmental science or engineering. Explore what doors open by seeing what can you do with an environmental science degree or researching environmental engineering degrees online.

By considering these online pathways, you can find programs tailored to your academic record, time frame, and career interests, helping you shape a technology-driven future.

Best Scientists Citing Yarin Gal

Trending Scientists

Recently Published Articles