World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
28040
World Ranking
7346
National Ranking
2

Pablo Arbeláez 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 Pablo Arbeláez 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: 113 publications — 12th percentile

12% of scientists in this discipline score the same or lower.

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

Pablo Arbeláez 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 Pablo Arbeláez 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

Pablo Arbeláez is a researcher affiliated with Universidad de Los Andes in Colombia. Their work spans multiple disciplines with a primary focus on computer science and medicine. Within these fields, their contributions cover subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology, Biomedical Engineering, and Radiology, Nuclear Medicine and Imaging.

Their research topics include:

  • Surgical Simulation and Training
  • Radiomics and Machine Learning in Medical Imaging
  • Advanced Neural Network Applications
  • Artificial Intelligence in Healthcare and Education
  • Human Pose and Action Recognition
  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning

Among their frequent co-authors are Laura Daza, Paola Ruiz Puentes, Cristina González, Bernard Ghanem, and María Escobar. These collaborations suggest interdisciplinary and sustained partnerships within their research environment.

They have published extensively in venues such as arXiv (Cornell University), Medical Image Analysis, Lecture Notes in Computer Science, bioRxiv (Cold Spring Harbor Laboratory), and Scientific Reports. The number of publications in these venues highlight consistent contributions particularly in preprint servers and peer-reviewed journals across computer science and medical disciplines.

Recent papers include:

  • "The Medical Segmentation Decathlon" (2022), Nature Communications
  • "An image J plugin for the high throughput image analysis of in vitro scratch wound healing assays" (2020), PLoS ONE
  • "Ego4D: Around the World in 3,000 Hours of Egocentric Video" (2022), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "An image J plugin for the high throughput image analysis of in vitro scratch wound healing assays" (2020), bioRxiv (Cold Spring Harbor Laboratory)
  • "Automatic seizure detection based on imaged-EEG signals through fully convolutional networks" (2020), Scientific Reports

Best Publications

  • Contour Detection and Hierarchical Image Segmentation

    P Arbeláez;M Maire;C Fowlkes;J Malik

  • Hypercolumns for object segmentation and fine-grained localization

    Bharath Hariharan;Pablo Arbelaez;Ross Girshick;Jitendra Malik

  • Learning Rich Features from RGB-D Images for Object Detection and Segmentation

    Saurabh Gupta;Ross B. Girshick;Pablo Andrés Arbeláez;Pablo Andrés Arbeláez;Jitendra Malik

  • Semantic contours from inverse detectors

    Bharath Hariharan;Pablo Arbelaez;Lubomir Bourdev;Subhransu Maji

  • Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

    Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer

  • Simultaneous Detection and Segmentation

    Bharath Hariharan;Pablo Andrés Arbeláez;Pablo Andrés Arbeláez;Ross B. Girshick;Jitendra Malik

  • Multiscale Combinatorial Grouping

    Pablo Arbeláez;Jordi Pont-Tuset;Jon Barron;Ferran Marques

  • The Medical Segmentation Decathlon

    Michela Antonelli;Annika Reinke;Spyridon Bakas;Keyvan Farahani

  • The 2017 DAVIS Challenge on Video Object Segmentation

    Jordi Pont-Tuset;Federico Perazzi;Sergi Caelles;Pablo Arbelaez

  • Perceptual Organization and Recognition of Indoor Scenes from RGB-D Images

    Saurabh Gupta;Pablo Arbelaez;Jitendra Malik

  • An image J plugin for the high throughput image analysis of in vitro scratch wound healing assays.

    Alejandra Suarez-Arnedo;Felipe Torres Figueroa;Camila Clavijo;Pablo Arbeláez

  • Multiscale Combinatorial Grouping for Image Segmentation and Object Proposal Generation

    Jordi Pont-Tuset;Pablo Arbelaez;Jonathan T.Barron;Ferran Marques

  • From contours to regions: An empirical evaluation

    Pablo Arbelaez;Michael Maire;Charless Fowlkes;Jitendra Malik

  • Using contours to detect and localize junctions in natural images

    M. Maire;P. Arbelaez;C. Fowlkes;J. Malik

  • Deep Retinal Image Understanding

    Kevis-Kokitsi Maninis;Jordi Pont-Tuset;Pablo Andrés Arbeláez;Luc J. Van Gool;Luc J. Van Gool

  • Recognition using regions

    Chunhui Gu;Joseph J Lim;Pablo Arbelaez;Jitendra Malik

  • Ego4D: Around the World in 3,000 Hours of Egocentric Video

    Kristen Grauman;Andrew Westbury;Eugene Byrne;Zachary Chavis

  • Semantic segmentation using regions and parts

    Pablo Arbelaez;Bharath Hariharan;Chunhui Gu;Saurabh Gupta

  • Indoor Scene Understanding with RGB-D Images: Bottom-up Segmentation, Object Detection and Semantic Segmentation

    Saurabh Gupta;Pablo Arbeláez;Ross Girshick;Jitendra Malik

  • Boundary Extraction in Natural Images Using Ultrametric Contour Maps

    P. Arbelaez

  • Aligning 3D models to RGB-D images of cluttered scenes

    Saurabh Gupta;Pablo Arbelaez;Ross Girshick;Jitendra Malik

Frequent Co-Authors

Jitendra Malik
Jitendra Malik University of California, Berkeley
Luc Van Gool
Luc Van Gool Institute for Computer Science, Artificial Intelligence and Technology (INSAIT)
Ross Girshick
Ross Girshick Facebook (United States)
Saurabh Gupta
Saurabh Gupta University of Illinois at Urbana-Champaign
Bernard Ghanem
Bernard Ghanem King Abdullah University of Science and Technology
Laurent D. Cohen
Laurent D. Cohen Paris Dauphine University
Tom Vercauteren
Tom Vercauteren King's College London
Klaus H. Maier-Hein
Klaus H. Maier-Hein German Cancer Research Center
Arlindo L. Oliveira
Arlindo L. Oliveira University of Lisbon
Steven E. Brenner
Steven E. Brenner University of California, Berkeley

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