World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
60
Citations
24491
World Ranking
3165
National Ranking
1534

Garrison W. Cottrell 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 Garrison W. Cottrell 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: 273 publications — 68th percentile

68% of scientists in this discipline score the same or lower.

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

Garrison W. Cottrell 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 Garrison W. Cottrell 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: 60 D-Index — 78th percentile

78% of scientists in this discipline score the same or lower.

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

Overview

Garrison W. Cottrell is affiliated with the University of California, San Diego in the United States. Their research primarily spans the field of Computer Science, with a focus on several subfields including Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology, Cognitive Neuroscience, and Signal Processing.

Their recent publications reflect a range of interdisciplinary interests interfacing deep learning and natural products, time series analysis, and safety systems. Selected recent papers include:

  • NPClassifier: A Deep Neural Network-Based Structural Classification Tool for Natural Products, 2021, Journal of Natural Products
  • A Convolutional Neural Network-Based Approach for the Rapid Annotation of Molecularly Diverse Natural Products, 2020, Journal of the American Chemical Society
  • ReZero is All You Need: Fast Convergence at Large Depth, 2020, arXiv (Cornell University)
  • Adversarial Joint-Learning Recurrent Neural Network for Incomplete Time Series Classification, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • FIgLib & SmokeyNet: Dataset and Deep Learning Model for Real-Time Wildland Fire Smoke Detection, 2022, Remote Sensing

The research topics covered in their work include:

  • Metabolomics and Mass Spectrometry Studies
  • Computational Drug Discovery Methods
  • Microbial Natural Products and Biosynthesis
  • Time Series Analysis and Forecasting
  • Domain Adaptation and Few-Shot Learning
  • Anomaly Detection Techniques and Applications
  • Fire Detection and Safety Systems

Frequent coauthors contributing to their research are William H. Gerwick, Hyun Woo Kim, Chen Zhang, Qianli Ma, and Sen Li. This network of collaboration supports a multidisciplinary approach across computational and biological sciences.

Garrison W. Cottrell's publications appear predominantly in venues such as the Proceedings of the AAAI Conference on Artificial Intelligence, arXiv (Cornell University), Journal of Natural Products, Remote Sensing, and the Journal of the American Chemical Society, indicating a blend of conference and journal contributions.

Best Publications

  • Behavior recognition via sparse spatio-temporal features

    P. Dollar;V. Rabaud;G. Cottrell;S. Belongie

  • Understanding Convolution for Semantic Segmentation

    Panqu Wang;Pengfei Chen;Ye Yuan;Ding Liu

  • SUN: A Bayesian framework for saliency using natural statistics.

    Lingyun Zhang;Matthew H. Tong;Tim K. Marks;Honghao Shan

  • A dual-stage attention-based recurrent neural network for time series prediction

    Yao Qin;Dongjin Song;Haifeng Cheng;Wei Cheng

  • Early lateralization and orientation tuning for face, word, and object processing in the visual cortex

    Bruno Rossion;Carrie A Joyce;Garrison W Cottrell;Michael J Tarr

  • Transmitting and Decoding Facial Expressions

    Marie L. Smith;Garrison W. Cottrell;FrédéAric Gosselin;Philippe G. Schyns

  • Connectionist models of face processing: A survey

    Dominique Valentin;Hervé Abdi;Hervé Abdi;Alice J. O'Toole;Garrison W. Cottrell

  • Two Fixations Suffice in Face Recognition

    Janet Hui-wen Hsiao;Garrison Cottrell

  • A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction

    Yao Qin;Dongjin Song;Haifeng Chen;Wei Cheng

  • Non-Linear Dimensionality Reduction

    David DeMers;Garrison W. Cottrell

  • NPClassifier: A Deep Neural Network-Based Structural Classification Tool for Natural Products.

    Hyun Woo Kim;Mingxun Wang;Christopher A. Leber;Louis-Félix Nothias

  • Color-to-Grayscale: Does the Method Matter in Image Recognition?

    Christopher Kanan;Garrison W. Cottrell

  • Automatic combination of multiple ranked retrieval systems

    Brian T. Bartell;Garrison W. Cottrell;Richard K. Belew

  • Fusion Via a Linear Combination of Scores

    Christopher C. Vogt;Garrison W. Cottrell

  • A Connectionist Approach to Word Sense Disambiguation

    Garrison W. Cottrell

  • Representing Face Images for Emotion Classification

    Curtis Padgett;Garrison W. Cottrell

  • EMPATH: A Neural Network that Categorizes Facial Expressions

    Matthew N. Dailey;Garrison W. Cottrell;Curtis Padgett;Ralph Adolphs

  • EMPATH: Face, Emotion, and Gender Recognition Using Holons

    Garrison W. Cottrell;Janet Metcalfe

  • SUN: Top-down saliency using natural statistics.

    Christopher Kanan;Mathew H. Tong;Lingyun Zhang;Garrison W. Cottrell

  • Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition.

    Yao Qin;Nicholas Carlini;Garrison W. Cottrell;Ian J. Goodfellow

  • Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition

    Yao Qin;Nicholas Carlini;Ian Goodfellow;Garrison Cottrell

Frequent Co-Authors

William H. Gerwick
William H. Gerwick University of California, San Diego
Julian McAuley
Julian McAuley University of California, San Diego
Richard K. Belew
Richard K. Belew University of California, San Diego
Martin I. Sereno
Martin I. Sereno San Diego State University
Terrence J. Sejnowski
Terrence J. Sejnowski Salk Institute for Biological Studies
Xiaohui Shen
Xiaohui Shen ByteDance
Colin Raffel
Colin Raffel University of Toronto
Zhe Lin
Zhe Lin Adobe Systems (United States)
William B. Kristan
William B. Kristan University of California, San Diego
Konstantinos Kamnitsas
Konstantinos Kamnitsas University of Oxford

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