World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
6154
World Ranking
12493
National Ranking
162

Suha Kwak 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 Suha Kwak 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: 128 publications — 18th percentile

18% of scientists in this discipline score the same or lower.

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

Suha Kwak 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 Suha Kwak 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: 33 D-Index — 13th percentile

13% of scientists in this discipline score the same or lower.

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

Best Publications

  • Learning Pixel-Level Semantic Affinity with Image-Level Supervision for Weakly Supervised Semantic Segmentation

    Unknown

  • Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural Network

    Seunghoon Hong;Tackgeun You;Suha Kwak;Bohyung Han

  • Weakly Supervised Learning of Instance Segmentation With Inter-Pixel Relations

    Unknown

  • Domain-Specific Batch Normalization for Unsupervised Domain Adaptation

    Woong-Gi Chang;Tackgeun You;Seonguk Seo;Suha Kwak

  • Proxy Anchor Loss for Deep Metric Learning

    Sungyeon Kim;Dongwon Kim;Minsu Cho;Suha Kwak

  • Unsupervised object discovery and localization in the wild: Part-based matching with bottom-up region proposals

    Minsu Cho;Suha Kwak;Cordelia Schmid;Jean Ponce

  • ReSTR: Convolution-free Referring Image Segmentation Using Transformers

    Unknown

  • Weakly Supervised Semantic Segmentation Using Web-Crawled Videos

    Seunghoon Hong;Donghun Yeo;Suha Kwak;Honglak Lee

  • Weakly Supervised Semantic Segmentation Using Superpixel Pooling Network

    Suha Kwak;Seunghoon Hong;Bohyung Han

  • MotionSqueeze: Neural Motion Feature Learning for Video Understanding

    Heeseung Kwon;Manjin Kim;Suha Kwak;Minsu Cho

  • Unsupervised Object Discovery and Tracking in Video Collections

    Suha Kwak;Minsu Cho;Ivan Laptev;Jean Ponce

  • Learning occlusion with likelihoods for visual tracking

    Suha Kwak;Woonhyun Nam;Bohyung Han;Joon Hee Han

  • Semi-supervised Semantic Segmentation with Error Localization Network

    Unknown

  • Generalized background subtraction based on hybrid inference by belief propagation and Bayesian filtering

    Suha Kwak;Taegyu Lim;Woonhyun Nam;Bohyung Han

  • Style Neophile: Constantly Seeking Novel Styles for Domain Generalization

    Unknown

  • Deep Metric Learning Beyond Binary Supervision

    Sungyeon Kim;Minkyo Seo;Ivan Laptev;Minsu Cho

  • Online multi-target tracking by large margin structured learning

    Suna Kim;Suha Kwak;Jan Feyereisl;Bohyung Han

  • Detector-Free Weakly Supervised Group Activity Recognition

    Unknown

  • FIFO: Learning Fog-invariant Features for Foggy Scene Segmentation

    Unknown

  • Learning Pixel-level Semantic Affinity with Image-level Supervision for Weakly Supervised Semantic Segmentation

    Unknown

Frequent Co-Authors

Minsu Cho
Minsu Cho Pohang University of Science and Technology
Bohyung Han
Bohyung Han Seoul National University
Ivan Laptev
Ivan Laptev Mohamed bin Zayed University of Artificial Intelligence
Jean Ponce
Jean Ponce École Normale Supérieure
Cordelia Schmid
Cordelia Schmid French Institute for Research in Computer Science and Automation - INRIA
Honglak Lee
Honglak Lee University of Michigan–Ann Arbor
Josef Sivic
Josef Sivic Czech Technical University in Prague
Léon Bottou
Léon Bottou Facebook (United States)
Seungjin Choi
Seungjin Choi Pohang University of Science and Technology
Stefan Lee
Stefan Lee Oregon State 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:

Best Scientists Citing Suha Kwak

Recently Published Articles