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Computer Science
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2026

D-Index & Metrics

Best Scientists

D-Index
168
Citations
243493
World Ranking
924
National Ranking
546

Computer Science

D-Index
169
Citations
255305
World Ranking
17
National Ranking
8

Trevor Darrell 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 Trevor Darrell 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: 633 publications — 97th percentile

97% of scientists in this discipline score the same or lower.

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

Trevor Darrell 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 Trevor Darrell 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: 169 D-Index — 100th percentile

100% 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

  • 2026 - Research.com Computer Science in United States Leader Award
  • 2025 - Research.com Best Scientists Award
  • 2025 - Research.com Computer Science in United States Leader Award
  • 2023 - Research.com Computer Science in United States Leader Award
  • 2022 - Research.com Computer Science in United States Leader Award

Overview

Trevor Darrell is affiliated with the University of California, Berkeley in the United States. Their research primarily focuses on various areas within computer science, particularly computer vision and artificial intelligence.

Their main fields of study include:

  • Computer Science

Within this domain, their subfields of specialization encompass:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Control and Systems Engineering
  • Signal Processing
  • Radiology, Nuclear Medicine and Imaging

Trevor Darrell's work covers a range of topics, with notable emphasis on:

  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Human Pose and Action Recognition
  • Advanced Neural Network Applications
  • Advanced Image and Video Retrieval Techniques
  • Topic Modeling
  • Generative Adversarial Networks and Image Synthesis

Their publication record includes contributions in both conferences and open-access repositories. Frequent venues for their publications are:

  • arXiv (Cornell University)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Applied AI Letters
  • Lecture Notes in Computer Science

Recent papers authored or co-authored by Trevor Darrell include:

  • "A ConvNet for the 2020s" (2022), presented at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning" (2021), published at the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "Early Convolutions Help Transformers See Better" (2021), available on arXiv (Cornell University)
  • "Tent: Fully Test-time Adaptation by Entropy Minimization" (2020), available on arXiv (Cornell University)
  • "Contrastive Test-Time Adaptation" (2022), presented at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Trevor Darrell has frequently collaborated with several researchers, including:

  • Anna Rohrbach
  • Joseph E. Gonzalez
  • Roei Herzig
  • Amir Bar
  • Baifeng Shi

Best Publications

  • Fully convolutional networks for semantic segmentation

    Jonathan Long;Evan Shelhamer;Trevor Darrell

  • Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

    Ross Girshick;Jeff Donahue;Trevor Darrell;Jitendra Malik

  • Caffe: Convolutional Architecture for Fast Feature Embedding

    Yangqing Jia;Evan Shelhamer;Jeff Donahue;Sergey Karayev

  • Fully Convolutional Networks for Semantic Segmentation

    Evan Shelhamer;Jonathan Long;Trevor Darrell

  • A ConvNet for the 2020s

    Unknown

  • Pfinder: real-time tracking of the human body

    C.R. Wren;A. Azarbayejani;T. Darrell;A.P. Pentland

  • Long-term recurrent convolutional networks for visual recognition and description

    Jeff Donahue;Lisa Anne Hendricks;Sergio Guadarrama;Marcus Rohrbach

  • Context Encoders: Feature Learning by Inpainting

    Deepak Pathak;Philipp Krahenbuhl;Jeff Donahue;Trevor Darrell

  • Adversarial Discriminative Domain Adaptation

    Eric Tzeng;Judy Hoffman;Kate Saenko;Trevor Darrell

  • DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

    Jeff Donahue;Yangqing Jia;Oriol Vinyals;Judy Hoffman

  • Region-Based Convolutional Networks for Accurate Object Detection and Segmentation

    Ross Girshick;Jeff Donahue;Trevor Darrell;Jitendra Malik

  • End-to-end training of deep visuomotor policies

    Sergey Levine;Chelsea Finn;Trevor Darrell;Pieter Abbeel

  • Adapting visual category models to new domains

    Kate Saenko;Brian Kulis;Mario Fritz;Trevor Darrell

  • Deep Domain Confusion: Maximizing for Domain Invariance

    Eric Tzeng;Judy Hoffman;Ning Zhang;Kate Saenko

  • CyCADA: Cycle-Consistent Adversarial Domain Adaptation

    Judy Hoffman;Eric Tzeng;Taesung Park;Jun-Yan Zhu

  • BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning

    Fisher Yu;Haofeng Chen;Xin Wang;Wenqi Xian

  • The pyramid match kernel: discriminative classification with sets of image features

    K. Grauman;T. Darrell

  • Curiosity-driven Exploration by Self-supervised Prediction

    Deepak Pathak;Pulkit Agrawal;Alexei A. Efros;Trevor Darrell

  • Long-Term Recurrent Convolutional Networks for Visual Recognition and Description

    Jeff Donahue;Lisa Anne Hendricks;Marcus Rohrbach;Subhashini Venugopalan

  • Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding

    Akira Fukui;Dong Huk Park;Daylen Yang;Anna Rohrbach

  • Integrated Person Tracking Using Stereo, Color, and Pattern Detection

    T. Darrell;G. Gordon;M. Harville;J. Woodfill

  • Adversarial Feature Learning

    Jeff Donahue;Philipp Krähenbühl;Trevor Darrell

Frequent Co-Authors

Kate Saenko
Kate Saenko Boston University
Marcus Rohrbach
Marcus Rohrbach Facebook (United States)
Judy Hoffman
Judy Hoffman Georgia Institute of Technology
Jeff Donahue
Jeff Donahue DeepMind (United Kingdom)
Fisher Yu
Fisher Yu ETH Zurich
Anna Rohrbach
Anna Rohrbach Technical University of Darmstadt
Louis-Philippe Morency
Louis-Philippe Morency Carnegie Mellon University
Yangqing Jia
Yangqing Jia Alibaba Group (China)
Sergey Levine
Sergey Levine University of California, Berkeley

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