World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
46
Citations
11792
World Ranking
6720
National Ranking
902

Qian Wang 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 Qian Wang 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: 220 publications — 53rd percentile

53% of scientists in this discipline score the same or lower.

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

Qian Wang 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 Qian Wang 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: 46 D-Index — 53rd percentile

53% 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

  • 2009 - Fellow of the American Society of Mechanical Engineers

Overview

Qian Wang is affiliated with Shanghai Jiao Tong University in China and has contributed extensively to the fields of medicine and computer science. Their research primarily involves the intersection of medical imaging, artificial intelligence, and advanced computational methods.

Wang's work spans several main fields of study, including:

  • Medicine
  • Computer Science

Their subfields of specialization include:

  • Computer Vision and Pattern Recognition
  • Radiology, Nuclear Medicine and Imaging
  • Artificial Intelligence
  • Cognitive Neuroscience
  • Biomedical Engineering

The main topics addressed in Wang's research encompass:

  • Radiomics and Machine Learning in Medical Imaging
  • Medical Image Segmentation Techniques
  • AI in cancer detection
  • Functional Brain Connectivity Studies
  • Advanced MRI Techniques and Applications
  • Advanced Neuroimaging Techniques and Applications
  • Advanced Neural Network Applications

Among the frequent publication venues where Wang's research can be found are:

  • UNC Libraries
  • arXiv (Cornell University)
  • IEEE Transactions on Medical Imaging
  • Medical Image Analysis
  • Frontiers in Neuroscience

Frequent collaborators of Wang include:

  • Dinggang Shen
  • Lichi Zhang
  • Zhenrong Shen
  • Guorong Wu
  • Zhong Xue

Selected papers authored or co-authored by Wang include:

  • "Dual-Sampling Attention Network for Diagnosis of COVID-19 From Community Acquired Pneumonia," 2020, IEEE Transactions on Medical Imaging
  • "Transformers in medical image analysis," 2022, Intelligent Medicine
  • "Learning Hierarchical Attention for Weakly-Supervised Chest X-Ray Abnormality Localization and Diagnosis," 2020, IEEE Transactions on Medical Imaging
  • "Segmentation and Classification in Digital Pathology for Glioma Research: Challenges and Deep Learning Approaches," 2020, Frontiers in Neuroscience
  • "Interactive computer-aided diagnosis on medical image using large language models," 2024, Communications Engineering

Wang was awarded the title of Fellow of the American Society of Mechanical Engineers in 2009.

Best Publications

  • Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation, and Diagnosis for COVID-19

    Feng Shi;Jun Wang;Jun Shi;Ziyan Wu

  • Medical Image Synthesis with Context-Aware Generative Adversarial Networks

    Dong Nie;Roger Trullo;Jun Lian;Caroline Petitjean

  • Medical Image Synthesis with Deep Convolutional Adversarial Networks

    Dong Nie;Roger Trullo;Jun Lian;Li Wang

  • A Multi-Organ Nucleus Segmentation Challenge

    Neeraj Kumar;Ruchika Verma;Deepak Anand;Yanning Zhou

  • Dual-Sampling Attention Network for Diagnosis of COVID-19 From Community Acquired Pneumonia

    Xi Ouyang;Jiayu Huo;Liming Xia;Fei Shan

  • Scalable High-Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning

    Guorong Wu;Minjeong Kim;Qian Wang;Brent C. Munsell

  • Deep auto-context convolutional neural networks for standard-dose PET image estimation from low-dose PET/MRI

    Lei Xiang;Yu Qiao;Dong Nie;Le An

  • Machine learning of serum metabolic patterns encodes early-stage lung adenocarcinoma.

    Lin Huang;Lin Wang;Xiaomeng Hu;Sen Chen

  • Deformable Image Registration based on Similarity-Steered CNN Regression.

    Xiaohuan Cao;Jianhua Yang;Jun Zhang;Dong Nie

  • Multi-Channel 3D Deep Feature Learning for Survival Time Prediction of Brain Tumor Patients Using Multi-Modal Neuroimages

    Dong Nie;Junfeng Lu;Han Zhang;Ehsan Adeli

  • Deep embedding convolutional neural network for synthesizing CT image from T1-Weighted MR image.

    Lei Xiang;Qian Wang;Dong Nie;Lichi Zhang

  • Interleaved 3D-CNNs for joint segmentation of small-volume structures in head and neck CT images

    Xuhua Ren;Lei Xiang;Dong Nie;Yeqin Shao

  • Unsupervised deep feature learning for deformable registration of MR brain images

    Guorong Wu;Minjeong Kim;Qian Wang;Yaozong Gao

  • Integration of Network Topological and Connectivity Properties for Neuroimaging Classification

    Biao Jie;Daoqiang Zhang;Wei Gao;Qian Wang

  • Deep-Learning-Based Multi-Modal Fusion for Fast MR Reconstruction

    Lei Xiang;Yong Chen;Weitang Chang;Yiqiang Zhan

  • Adversarial learning for mono- or multi-modal registration

    Jingfan Fan;Xiaohuan Cao;Qian Wang;Pew Thian Yap

  • SharpMean: groupwise registration guided by sharp mean image and tree-based registration.

    Guorong Wu;Hongjun Jia;Qian Wang;Dinggang Shen

  • ABSORB: Atlas Building by Self-organized Registration and Bundling.

    Hongjun Jia;Guorong Wu;Qian Wang;Dinggang Shen

  • Deformable Image Registration Using a Cue-Aware Deep Regression Network

    Xiaohuan Cao;Jianhua Yang;Jun Zhang;Qian Wang

  • A generative probability model of joint label fusion for multi-atlas based brain segmentation.

    Guorong Wu;Qian Wang;Daoqiang Zhang;Feiping Nie

Frequent Co-Authors

Dinggang Shen
Dinggang Shen ShanghaiTech University
Guorong Wu
Guorong Wu University of North Carolina at Chapel Hill
Pew Thian Yap
Pew Thian Yap University of North Carolina at Chapel Hill
Yaozong Gao
Yaozong Gao United Imaging Healthcare (China)
Han Zhang
Han Zhang ShanghaiTech University
Dong Nie
Dong Nie University of North Carolina at Chapel Hill
Weili Lin
Weili Lin University of North Carolina at Chapel Hill
Feng Shi
Feng Shi United Imaging Intelligence (China)
Dagan Feng
Dagan Feng University of Sydney
Yinghuan Shi
Yinghuan Shi Nanjing University

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