World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
13703
World Ranking
9047
National Ranking
279

Munawar Hayat 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 Munawar Hayat 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: 143 publications — 24th percentile

24% of scientists in this discipline score the same or lower.

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

Munawar Hayat 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 Munawar Hayat 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: 40 D-Index — 37th percentile

37% of scientists in this discipline score the same or lower.

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

Overview

Munawar Hayat is affiliated with Monash University in Australia and specializes in the field of Computer Science, with a focus on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Media Technology, and Human-Computer Interaction.

Their research covers a range of topics including:

  • Advanced Image Processing Techniques
  • Advanced Neural Network Applications
  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Human Pose and Action Recognition
  • Generative Adversarial Networks and Image Synthesis
  • Image and Signal Denoising Methods

Munawar Hayat has contributed to various publication venues with frequent publications in:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Medical Image Analysis

Recent papers by Munawar Hayat include:

  • Restormer: Efficient Transformer for High-Resolution Image Restoration, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Transformers in medical imaging: A survey, 2023, Medical Image Analysis
  • Learning Enriched Features for Fast Image Restoration and Enhancement, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Intriguing Properties of Vision Transformers, 2021, arXiv (Cornell University)
  • Restormer: Efficient Transformer for High-Resolution Image Restoration, 2021, arXiv (Cornell University)

The scientist has collaborated frequently with several co-authors, including:

  • Fahad Shahbaz Khan
  • Syed Waqas Zamir
  • Abhinav Dhall
  • Salman Khan
  • Aditya Arora

Best Publications

  • Restormer: Efficient Transformer for High-Resolution Image Restoration

    Unknown

  • Multi-Stage Progressive Image Restoration

    Syed Waqas Zamir;Aditya Arora;Salman Khan;Munawar Hayat

  • Transformers in Medical Imaging: A Survey

    Unknown

  • Cost-Sensitive Learning of Deep Feature Representations From Imbalanced Data

    Salman H. Khan;Munawar Hayat;Mohammed Bennamoun;Ferdous A. Sohel

  • Learning Enriched Features for Real Image Restoration and Enhancement

    Syed Waqas Zamir;Aditya Arora;Salman H. Khan;Munawar Hayat

  • Learning Enriched Features for Fast Image Restoration and Enhancement

    Unknown

  • CycleISP: Real Image Restoration via Improved Data Synthesis

    Syed Waqas Zamir;Aditya Arora;Salman Khan;Munawar Hayat

  • Intriguing Properties of Vision Transformers

    Muhammad Muzammal Naseer;Kanchana Ranasinghe;Salman H. Khan;Munawar Hayat

  • Intriguing Properties of Vision Transformers

    Muzammal Naseer;Kanchana Ranasinghe;Salman Khan;Munawar Hayat

  • A Self-supervised Approach for Adversarial Robustness

    Muzammal Naseer;Salman Khan;Munawar Hayat;Fahad Shahbaz Khan

  • Transformers in Vision: A Survey

    Salman H. Khan;Muzammal Naseer;Munawar Hayat;Syed Waqas Zamir

  • Deep Reconstruction Models for Image Set Classification

    Munawar Hayat;Mohammed Bennamoun;Senjian An

  • Restormer: Efficient Transformer for High-Resolution Image Restoration.

    Syed Waqas Zamir;Aditya Arora;Salman H. Khan;Munawar Hayat

  • A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation

    Unknown

  • Striking the Right Balance With Uncertainty

    Salman Khan;Munawar Hayat;Syed Waqas Zamir;Jianbing Shen

  • Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks

    Aamir Mustafa;Salman Khan;Munawar Hayat;Roland Goecke

  • A Discriminative Representation of Convolutional Features for Indoor Scene Recognition

    Salman H. Khan;Munawar Hayat;Mohammed Bennamoun;Roberto Togneri

  • Deep learning based synthesis of MRI, CT and PET: Review and analysis

    Unknown

  • An efficient 3D face recognition approach using local geometrical signatures

    Yinjie Lei;Mohammed Bennamoun;Munawar Hayat;Yulan Guo

  • NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

    Unknown

  • Image Super-Resolution as a Defense Against Adversarial Attacks

    Aamir Mustafa;Salman H. Khan;Munawar Hayat;Jianbing Shen

  • A Two-Phase Weighted Collaborative Representation for 3D partial face recognition with single sample

    Yinjie Lei;Yulan Guo;Munawar Hayat;Mohammed Bennamoun

  • Regularization of deep neural networks with spectral dropout

    Salman H. Khan;Salman H. Khan;Munawar Hayat;Fatih Porikli

  • Learning Non-linear Reconstruction Models for Image Set Classification

    Munawar Hayat;Mohammed Bennamoun;Senjian An

  • NTIRE 2021 NonHomogeneous Dehazing Challenge Report

    Codruta O. Ancuti;Cosmin Ancuti;Florin-Alexandru Vasluianu;Radu Timofte

  • A Spatial Layout and Scale Invariant Feature Representation for Indoor Scene Classification

    Munawar Hayat;Salman H. Khan;Mohammed Bennamoun;Senjian An

  • Random Path Selection for Continual Learning

    Jathushan Rajasegaran;Munawar Hayat;Salman H. Khan;Fahad Shahbaz Khan

  • Gaussian Affinity for Max-Margin Class Imbalanced Learning

    Munawar Hayat;Salman Khan;Syed Waqas Zamir;Jianbing Shen

  • Self-supervised Knowledge Distillation for Few-shot Learning

    Jathushan Rajasegaran;Salman H. Khan;Munawar Hayat;Fahad Shahbaz Khan

  • Striking the Right Balance with Uncertainty

    Salman Khan;Munawar Hayat;Waqas Zamir;Jianbing Shen

Frequent Co-Authors

Mohammed Bennamoun
Mohammed Bennamoun University of Western Australia
Ling Shao
Ling Shao Terminus International
Fahad Shahbaz Khan
Fahad Shahbaz Khan Mohamed bin Zayed University of Artificial Intelligence
Jianbing Shen
Jianbing Shen University of Macau
Roland Goecke
Roland Goecke University of New South Wales
Ferdous Sohel
Ferdous Sohel Murdoch University
Roberto Togneri
Roberto Togneri University of Western Australia
Salman Khan
Salman Khan Mohamed bin Zayed University of Artificial Intelligence
Nick Barnes
Nick Barnes Australian National University
Stefano Berretti
Stefano Berretti University of Florence

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