World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
9996
World Ranking
10997
National Ranking
147

Basura Fernando 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 Basura Fernando 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: 107 publications — 11th percentile

11% of scientists in this discipline score the same or lower.

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

Basura Fernando 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 Basura Fernando 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: 36 D-Index — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Overview

Basura Fernando is affiliated with the Agency for Science, Technology and Research in Singapore and specializes in computer science with a focus on computer vision and artificial intelligence. Their work primarily involves advancing machine learning techniques related to human pose and action recognition, video analysis, and multimodal machine learning applications.

The scientist has contributed notably to several key topics, including:

  • Multimodal Machine Learning Applications
  • Human Pose and Action Recognition
  • Anomaly Detection Techniques and Applications
  • Domain Adaptation and Few-Shot Learning
  • Topic Modeling
  • Advanced Neural Network Applications
  • Video Analysis and Summarization

Basura Fernando's research has appeared in a range of publication venues. The most frequent outlets include:

  • arXiv (Cornell University)
  • IEEE Transactions on Image Processing
  • International Journal of Computer Vision
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

The scientist has co-authored work with several frequent collaborators, such as:

  • Debaditya Roy
  • Hakan Bilen
  • Arushi Goel
  • Cheston Tan
  • Frank Keller

Recent notable publications from Basura Fernando include:

  • "Forecasting Future Action Sequences With Attention: A New Approach to Weakly Supervised Action Forecasting" (2020), IEEE Transactions on Image Processing
  • "Action Anticipation Using Pairwise Human-Object Interactions and Transformers" (2021), IEEE Transactions on Image Processing
  • "Not All Relations are Equal: Mining Informative Labels for Scene Graph Generation" (2022), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Action anticipation using latent goal learning" (2022), 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • "Long-term Action Forecasting Using Multi-headed Attention-based Variational Recurrent Neural Networks" (2022), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Their publications demonstrate a consistent focus on advancing methods for forecasting and anticipating human actions, often leveraging attention mechanisms and transformer models. The breadth of work includes both theoretical innovations and applications relevant to computer vision systems designed to interpret complex scenes and human-object interactions.

Best Publications

  • SPICE: Semantic Propositional Image Caption Evaluation

    Peter Anderson;Basura Fernando;Mark Johnson;Stephen Gould

  • Unsupervised Visual Domain Adaptation Using Subspace Alignment

    Basura Fernando;Amaury Habrard;Marc Sebban;Tinne Tuytelaars

  • Dynamic Image Networks for Action Recognition

    Hakan Bilen;Basura Fernando;Efstratios Gavves;Andrea Vedaldi

  • Modeling video evolution for action recognition

    Basura Fernando;Efstratios Gavves;M. Jose Oramas;Amir Ghodrati

  • Guiding the Long-Short Term Memory Model for Image Caption Generation

    Xu Jia;Efstratios Gavves;Basura Fernando;Tinne Tuytelaars

  • Self-Supervised Video Representation Learning with Odd-One-Out Networks

    Basura Fernando;Hakan Bilen;Efstratios Gavves;Stephen Gould

  • Rank Pooling for Action Recognition

    Basura Fernando;Efstratios Gavves;M Jose Oramas Oramas;Amir Ghodrati

  • Action Recognition with Dynamic Image Networks

    Hakan Bilen;Basura Fernando;Efstratios Gavves;Andrea Vedaldi

  • Face Super-resolution Guided by Facial Component Heatmaps

    Xin Yu;Basura Fernando;Bernard Ghanem;Fatih Porikli

  • Fine-Grained Categorization by Alignments

    E. Gavves;B. Fernando;C. G. M. Snoek;A. W. M. Smeulders

  • Guided Open Vocabulary Image Captioning with Constrained Beam Search

    Peter Anderson;Basura Fernando;Mark Johnson;Stephen Gould

  • Super-Resolving Very Low-Resolution Face Images with Supplementary Attributes

    Xin Yu;Basura Fernando;Richard Hartley;Fatih Porikli

  • Encouraging LSTMs to Anticipate Actions Very Early

    Mohammad Sadegh Aliakbarian;Fatemeh Sadat Saleh;Mathieu Salzmann;Basura Fernando

  • On Differentiating Parameterized Argmin and Argmax Problems with Application to Bi-level Optimization

    Stephen Gould;Basura Fernando;Anoop Cherian;Peter Anderson

  • Discriminative Hierarchical Rank Pooling for Activity Recognition

    Basura Fernando;Peter Anderson;Marcus Hutter;Stephen Gould

  • Discriminative feature fusion for image classification

    Basura Fernando;Elisa Fromont;Damien Muselet;Marc Sebban

  • Effective use of frequent itemset mining for image classification

    Basura Fernando;Elisa Fromont;Tinne Tuytelaars

  • Mining Mid-level Features for Image Classification

    Basura Fernando;Elisa Fromont;Tinne Tuytelaars

  • Guiding Long-Short Term Memory for Image Caption Generation.

    Xu Jia;Efstratios Gavves;Basura Fernando;Tinne Tuytelaars

  • Learning end-to-end video classification with rank-pooling

    Basura Fernando;Stephen Gould

Frequent Co-Authors

Stephen Gould
Stephen Gould Australian National University
Efstratios Gavves
Efstratios Gavves University of Amsterdam
Hakan Bilen
Hakan Bilen University of Edinburgh
Anoop Cherian
Anoop Cherian Mitsubishi Electric (United States)
Richard Hartley
Richard Hartley Australian National University
Mehrtash Harandi
Mehrtash Harandi Monash University
Lars Petersson
Lars Petersson Commonwealth Scientific and Industrial Research Organisation
Mathieu Salzmann
Mathieu Salzmann École Polytechnique Fédérale de Lausanne
Fatih Porikli
Fatih Porikli Australian National 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

Exploring online options can open up more flexible and affordable routes for studying Computer Science in the USA. Many students start with an online associate degree, which provides foundational knowledge and can often be transferred toward a bachelor’s program.

For those concerned about affordability, choosing from affordable online degree programs can help reduce student debt while earning a respected qualification. Online learning has come a long way and many reputable schools now offer budget-friendly courses.

If your GPA isn’t as high as you’d like, don’t worry. There are best online colleges that accept low gpa, providing more opportunities for those who might need a second chance. Such institutions make quality education accessible to a broader range of students.

Finally, pursuing Computer Science can lead to diverse job roles—not unlike those available with other majors. To explore alternative fields, check out potential jobs for environmental science majors to see how interdisciplinary skills can expand your career pathways.

Best Scientists Citing Basura Fernando

Trending Scientists

Recently Published Articles