World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
17474
World Ranking
6995
National Ranking
35

Salman Khan 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 Salman Khan 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: 91 publications — 6th percentile

6% of scientists in this discipline score the same or lower.

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

Salman Khan 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 Salman Khan 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: 45 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Overview

Salman Khan is affiliated with Mohamed bin Zayed University of Artificial Intelligence in the United Arab Emirates. Their research primarily focuses on computer science with a particular emphasis on computer vision and pattern recognition.

Their work spans several subfields including:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Media Technology
  • Radiology, Nuclear Medicine and Imaging
  • Atmospheric Science

The main topics covered in their publications include:

  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications
  • Multimodal Machine Learning Applications
  • Adversarial Robustness in Machine Learning
  • Advanced Image Processing Techniques
  • Advanced Image and Video Retrieval Techniques
  • Anomaly Detection Techniques and Applications

Salman Khan has contributed extensively to academic literature, with frequent publications in venues such as:

  • 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)
  • ACM Computing Surveys

Among their recent papers are:

  • Learning Enriched Features for Fast Image Restoration and Enhancement (2022, IEEE Transactions on Pattern Analysis and Machine Intelligence)
  • A Deep Journey into Super-resolution (2020, ACM Computing Surveys)
  • Intriguing Properties of Vision Transformers (2021, arXiv (Cornell University))
  • Transformers in Remote Sensing: A Survey (2023, Remote Sensing)
  • UNETR++: Delving Into Efficient and Accurate 3D Medical Image Segmentation (2024, IEEE Transactions on Medical Imaging)

Collaboration has been a significant aspect of their research, working frequently with co-authors such as:

  • Fahad Shahbaz Khan
  • Muzammal Naseer
  • Rao Muhammad Anwer
  • Hisham Cholakkal
  • Syed Waqas Zamir

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

  • 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

  • Towards Open World Object Detection

    K J Joseph;Salman Khan;Fahad Shahbaz Khan;Vineeth N Balasubramanian

  • A Deep Journey into Super-resolution: A Survey

    Saeed Anwar;Salman Khan;Nick Barnes

  • CycleISP: Real Image Restoration via Improved Data Synthesis

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

  • A Unified Approach for Conventional Zero-Shot, Generalized Zero-Shot, and Few-Shot Learning

    Shafin Rahman;Salman Khan;Fatih Porikli

  • Automatic Shadow Detection and Removal from a Single Image

    Salman H. Khan;Mohammed Bennamoun;Ferdous Sohel;Roberto Togneri

  • Forest Change Detection in Incomplete Satellite Images With Deep Neural Networks

    Salman H. Khan;Xuming He;Fatih Porikli;Mohammed Bennamoun

  • Spatio-temporal Relation Modeling for Few-shot Action Recognition

    Unknown

  • Automatic Feature Learning for Robust Shadow Detection

    Salman Hameed Khan;Mohammed Bennamoun;Ferdous Sohel;Roberto Togneri

  • Fine-Grained Recognition: Accounting for Subtle Differences between Similar Classes

    Guolei Sun;Hisham Cholakkal;Salman H. Khan;Fahad Shahbaz Khan

  • Local Gradients Smoothing: Defense Against Localized Adversarial Attacks

    Muzammal Naseer;Salman Khan;Fatih Porikli

  • Ground-to-Aerial Image Geo-Localization With a Hard Exemplar Reweighting Triplet Loss

    Sudong Cai;Yulan Guo;Salman Khan;Jiwei Hu

  • Self-charging wearables for continuous health monitoring

    Jiyong Kim;Salman Khan;Peng Wu;Sungjin Park

  • Indoor Scene Understanding in 2.5/3D for Autonomous Agents: A Survey

    Muhammad Muzammal Naseer;Salman H. Khan;Fatih Porikli

  • Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning

    Mamshad Nayeem Rizve;Salman Khan;Fahad Shahbaz Khan;Mubarak Shah

  • DeepSmoke: Deep learning model for smoke detection and segmentation in outdoor environments

    Salman Khan;Salman Khan;Khan Muhammad;Tanveer Hussain;Javier Del Ser

  • Improved Visual-Semantic Alignment for Zero-Shot Object Detection

    Shafin Rahman;Salman H. Khan;Nick Barnes

  • Regularization of deep neural networks with spectral dropout

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

  • NTIRE 2019 Challenge on Real Image Denoising: Methods and Results

    Abdelrahman Abdelhamed;Radu Timofte;Michael S. Brown;Songhyun Yu

  • Transductive Learning for Zero-Shot Object Detection

    Shafin Rahman;Salman Khan;Nick Barnes

Frequent Co-Authors

Fahad Shahbaz Khan
Fahad Shahbaz Khan Mohamed bin Zayed University of Artificial Intelligence
Mohammed Bennamoun
Mohammed Bennamoun University of Western Australia
Ming-Hsuan Yang
Ming-Hsuan Yang University of California, Merced
Nick Barnes
Nick Barnes Australian National University
Radu Timofte
Radu Timofte University of Wurzburg
Fatih Porikli
Fatih Porikli Australian National University
Marie-Paule Cani
Marie-Paule Cani École Polytechnique
Christian Micheloni
Christian Micheloni University of Udine
Wan-Chi Siu
Wan-Chi Siu Hong Kong Polytechnic University
Wangmeng Zuo
Wangmeng Zuo Harbin Institute of Technology

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