World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
62
Citations
15147
World Ranking
2903
National Ranking
1428

Marios Savvides 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 Marios Savvides 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: 350 publications — 82nd percentile

82% of scientists in this discipline score the same or lower.

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

Marios Savvides 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 Marios Savvides 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: 62 D-Index — 80th percentile

80% of scientists in this discipline score the same or lower.

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

Overview

Marios Savvides is affiliated with Carnegie Mellon University in the United States. Their research is primarily situated in Computer Science, with an emphasis on areas such as Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Neurology, and Signal Processing.

Their work covers a range of topics, including:

  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications
  • Multimodal Machine Learning Applications
  • Advanced Image and Video Retrieval Techniques
  • Face recognition and analysis
  • Machine Learning and Data Classification
  • Machine Learning and ELM

Marios Savvides has published extensively, with a total of 111 publications in their main field. They have contributed significantly to venues such as:

  • arXiv (Cornell University)
  • Alzheimer's & Dementia
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • NeuroImage
  • Artificial Intelligence Review

Recent papers authored or coauthored by Savvides include:

  • Deep reinforcement learning in computer vision: a comprehensive survey, 2021, Artificial Intelligence Review
  • FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning, 2022, arXiv (Cornell University)
  • Partial Is Better Than All: Revisiting Fine-tuning Strategy for Few-shot Learning, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning, 2023, arXiv (Cornell University)
  • Un-mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning, 2022, Proceedings of the AAAI Conference on Artificial Intelligence

Frequent collaborators include:

  • Zhiqiang Shen
  • Zechun Liu
  • Kwang-Ting Cheng
  • Chenchen Zhu
  • Fangyi Chen

Best Publications

  • Feature Selective Anchor-Free Module for Single-Shot Object Detection

    Chenchen Zhu;Yihui He;Marios Savvides

  • Bounding Box Regression With Uncertainty for Accurate Object Detection

    Yihui He;Chenchen Zhu;Jianren Wang;Marios Savvides

  • Cancelable biometric filters for face recognition

    M. Savvides;B.V.K. Vijaya Kumar;P.K. Khosla

  • ReActNet: Towards Precise Binary Neural Network with Generalized Activation Functions

    Zechun Liu;Zhiqiang Shen;Marios Savvides;Kwang-Ting Cheng

  • CMS-RCNN: Contextual Multi-Scale Region-Based CNN for Unconstrained Face Detection

    Chenchen Zhu;Yutong Zheng;Khoa Luu;Marios Savvides

  • Local Binary Convolutional Neural Networks

    Felix Juefei-Xu;Vishnu Naresh Boddeti;Marios Savvides

  • Semantic Relation Reasoning for Shot-Stable Few-Shot Object Detection

    Chenchen Zhu;Fangyi Chen;Uzair Ahmed;Zhiqiang Shen

  • Deep reinforcement learning in computer vision: a comprehensive survey

    Ngan Le;Ngan Le;Vidhiwar Singh Rathour;Vidhiwar Singh Rathour;Kashu Yamazaki;Kashu Yamazaki;Khoa Luu;Khoa Luu

  • Ring Loss: Convex Feature Normalization for Face Recognition

    Yutong Zheng;Dipan K. Pal;Marios Savvides

  • A Bayesian Approach to Deformed Pattern Matching of Iris Images

    J. Thornton;M. Savvides;V. Kumar

  • FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning

    Unknown

  • Illumination normalization using logarithm transforms for face authentication

    Marios Savvides;B. V. K. Vijaya Kumar

  • Correlation Pattern Recognition for Face Recognition

    B.V.K.V. Kumar;M. Savvides;Chunyan Xie

  • Investigating age invariant face recognition based on periocular biometrics

    Felix Juefei-Xu;Khoa Luu;Marios Savvides;Tien D. Bui

  • Unconstrained Pose-Invariant Face Recognition Using 3D Generic Elastic Models

    U. Prabhu;Jingu Heo;M. Savvides

  • Multiple Scale Faster-RCNN Approach to Driver’s Cell-Phone Usage and Hands on Steering Wheel Detection

    T. Hoang Ngan Le;Yutong Zheng;Chenchen Zhu;Khoa Luu

  • Soft Anchor-Point Object Detection

    Chenchen Zhu;Fangyi Chen;Zhiqiang Shen;Marios Savvides

  • NIR-VIS heterogeneous face recognition via cross-spectral joint dictionary learning and reconstruction

    Felix Juefei-Xu;Dipan K. Pal;Marios Savvides

  • Eigenphases vs eigenfaces

    M. Savvides;B.V.K.V. Kumar;P.K. Khosla

  • Biometric authentication on iPhone and Android: Usability, perceptions, and influences on adoption

    Rasekhar Bhagavatula;Blase Ur;Kevin Iacovino;Su Mon Kywe

  • How to Generate Spoofed Irises From an Iris Code Template

    S Venugopalan;M Savvides

Frequent Co-Authors

B. V. K. Vijaya Kumar
B. V. K. Vijaya Kumar Carnegie Mellon University
Felix Juefei-Xu
Felix Juefei-Xu Facebook (United States)
Pradeep K. Khosla
Pradeep K. Khosla University of California, San Diego
Kwang-Ting Cheng
Kwang-Ting Cheng Hong Kong University of Science and Technology
Tien D. Bui
Tien D. Bui Concordia University
Ching Y. Suen
Ching Y. Suen Concordia University
Robert M. Friedman
Robert M. Friedman Oregon Health & Science University
Thomas S. Huang
Thomas S. Huang University of Illinois at Urbana-Champaign
B. Yegnanarayana
B. Yegnanarayana International Institute of Information Technology, Hyderabad

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