World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
86
Citations
37329
World Ranking
755
National Ranking
402

Nuno Vasconcelos 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 Nuno Vasconcelos 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: 285 publications — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Nuno Vasconcelos 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 Nuno Vasconcelos 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: 86 D-Index — 95th percentile

95% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2017 - IEEE Fellow For contributions to computer vision, image processing, and multimedia
  • 2005 - Hellman Fellow

Overview

Nuno Vasconcelos is affiliated with the University of California, San Diego in the United States. Their research primarily spans the field of Computer Science, with extensive work in Computer Vision and Pattern Recognition, and Artificial Intelligence. Additional subfields include Computational Mechanics, Biomedical Engineering, and Radiology, Nuclear Medicine and Imaging.

The scientist's research topics cover a variety of areas, including:

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

Vasconcelos has published numerous papers in leading venues. Some recent notable publications are:

  • "A fully integrated wearable ultrasound system to monitor deep tissues in moving subjects" (2023), published in Nature Biotechnology
  • "Class-Incremental Learning with Strong Pre-trained Models" (2022), presented at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "MicroNet: Improving Image Recognition with Extremely Low FLOPs" (2021), at the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "GistNet: a Geometric Structure Transfer Network for Long-Tailed Recognition" (2021), also at ICCV 2021
  • "Contrastive Learning with Adversarial Examples" (2020), published on arXiv (Cornell University)

They frequently publish in venues such as:

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

The scientist has collaborated extensively with several frequent coauthors, including:

  • Chih-Hui Ho
  • Yunsheng Li
  • Tz-Ying Wu
  • Jiteng Mu
  • Yinpeng Chen

Nuno Vasconcelos has received the IEEE Fellow recognition in 2017 for contributions to computer vision, image processing, and multimedia. They were also awarded the Hellman Fellowship in 2005.

Best Publications

  • Cascade R-CNN: Delving Into High Quality Object Detection

    Zhaowei Cai;Nuno Vasconcelos

  • A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection

    Zhaowei Cai;Quanfu Fan;Rogério Schmidt Feris;Nuno Vasconcelos

  • Cascade R-CNN: High Quality Object Detection and Instance Segmentation

    Zhaowei Cai;Nuno Vasconcelos

  • Anomaly detection in crowded scenes

    Vijay Mahadevan;Weixin Li;Viral Bhalodia;Nuno Vasconcelos

  • A new approach to cross-modal multimedia retrieval

    Nikhil Rasiwasia;Jose Costa Pereira;Emanuele Coviello;Gabriel Doyle

  • Privacy preserving crowd monitoring: Counting people without people models or tracking

    A.B. Chan;Z.-S.J. Liang;N. Vasconcelos

  • Supervised Learning of Semantic Classes for Image Annotation and Retrieval

    G. Carneiro;A.B. Chan;P.J. Moreno;N. Vasconcelos

  • Anomaly Detection and Localization in Crowded Scenes

    Weixin Li;Vijay Mahadevan;Nuno Vasconcelos

  • Bidirectional Learning for Domain Adaptation of Semantic Segmentation

    Yunsheng Li;Lu Yuan;Nuno Vasconcelos

  • A Kullback-Leibler Divergence Based Kernel for SVM Classification in Multimedia Applications

    Pedro J. Moreno;Purdy P. Ho;Nuno Vasconcelos

  • Modeling, Clustering, and Segmenting Video with Mixtures of Dynamic Textures

    A.B. Chan;N. Vasconcelos

  • Deep Learning with Low Precision by Half-Wave Gaussian Quantization

    Zhaowei Cai;Xiaodong He;Jian Sun;Nuno Vasconcelos

  • Bayesian Poisson regression for crowd counting

    Antoni B. Chan;Nuno Vasconcelos

  • Spatiotemporal Saliency in Dynamic Scenes

    V. Mahadevan;N. Vasconcelos

  • Counting People With Low-Level Features and Bayesian Regression

    A. B. Chan;N. Vasconcelos

  • On the Role of Correlation and Abstraction in Cross-Modal Multimedia Retrieval

    Jose Costa Pereira;Emanuele Coviello;Gabriel Doyle;Nikhil Rasiwasia

  • Learning Complexity-Aware Cascades for Deep Pedestrian Detection

    Zhaowei Cai;Mohammad Saberian;Nuno Vasconcelos

  • Discriminant Saliency, the Detection of Suspicious Coincidences, and Applications to Visual Recognition

    Dashan Gao;Sunhyoung Han;N. Vasconcelos

  • On the plausibility of the discriminant center-surround hypothesis for visual saliency.

    Dashan Gao;Vijay Mahadevan;Nuno Vasconcelos

  • RESOUND: Towards Action Recognition Without Representation Bias

    Yingwei Li;Yi Li;Nuno Vasconcelos

  • Bridging the Gap: Query by Semantic Example

    Nikhil Rasiwasia;P.J. Moreno;N. Vasconcelos

Frequent Co-Authors

Antoni B. Chan
Antoni B. Chan City University of Hong Kong
Gustavo Carneiro
Gustavo Carneiro University of Surrey
Pedro J. Moreno
Pedro J. Moreno Google (United States)
Marc Niethammer
Marc Niethammer University of North Carolina at Chapel Hill
Gert R. G. Lanckriet
Gert R. G. Lanckriet University of California, San Diego
Harpreet Sawhney
Harpreet Sawhney Microsoft (United States)
Rogerio Feris
Rogerio Feris IBM (United States)
Jacqueline Kerr
Jacqueline Kerr University of California, San Diego
Pamela C. Cosman
Pamela C. Cosman University of California, San Diego

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