World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
66
Citations
20893
World Ranking
2290
National Ranking
314

Daoqiang Zhang 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 Daoqiang Zhang 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: 360 publications — 83rd percentile

83% of scientists in this discipline score the same or lower.

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

Daoqiang Zhang 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 Daoqiang Zhang 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: 66 D-Index — 84th percentile

84% 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

  • 2020 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to fuzzy clustering, dimensionality reduction, and medical image analysis

Overview

Daoqiang Zhang is affiliated with Nanjing University of Aeronautics and Astronautics in China. Their research spans several interdisciplinary fields, primarily focused on the intersection of computer science, medicine, and neuroscience.

The scientist has contributed extensively to topics such as functional brain connectivity studies, EEG and brain-computer interfaces, AI in cancer detection, brain tumor detection and classification, medical image segmentation techniques, radiomics and machine learning in medical imaging, and advanced neuroimaging techniques and applications.

Recent notable publications by Daoqiang Zhang include:

  • "Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification With Chest CT" (2020, IEEE Journal of Biomedical and Health Informatics)
  • "Dual Attention Multi-Instance Deep Learning for Alzheimer's Disease Diagnosis With Structural MRI" (2021, IEEE Transactions on Medical Imaging)
  • "A Survey on Deep Learning for Neuroimaging-Based Brain Disorder Analysis" (2020, Frontiers in Neuroscience)
  • "An Explainable 3D Residual Self-Attention Deep Neural Network for Joint Atrophy Localization and Alzheimer's Disease Diagnosis Using Structural MRI" (2021, IEEE Journal of Biomedical and Health Informatics)
  • "Cognitive Workload Recognition Using EEG Signals and Machine Learning: A Review" (2021, IEEE Transactions on Cognitive and Developmental Systems)

Frequent co-authors collaborating with Daoqiang Zhang include:

  • Wei Shao (45 collaborations)
  • Qi Zhu (41 collaborations)
  • Dinggang Shen (31 collaborations)
  • Fang Chen (30 collaborations)
  • Liang Sun (28 collaborations)

The scientist has published in various venues, demonstrating a breadth of dissemination channels predominantly oriented toward medical imaging and computational neuroscience. Key publication venues include:

  • UNC Libraries (30 publications)
  • arXiv (Cornell University) (30 publications)
  • IEEE Transactions on Medical Imaging (26 publications)
  • IEEE Transactions on Neural Systems and Rehabilitation Engineering (10 publications)
  • Medical Image Analysis (9 publications)

Daoqiang Zhang's primary fields of study are computer science, medicine, and neuroscience, with significant work also situated in specialized subfields including cognitive neuroscience, radiology, nuclear medicine and imaging, artificial intelligence, computer vision and pattern recognition, and biomedical engineering.

In recognition of contributions to the domains of fuzzy clustering, dimensionality reduction, and medical image analysis, Daoqiang Zhang was named a Fellow of the International Association for Pattern Recognition (IAPR) in 2020.

Best Publications

  • Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure

    Songcan Chen;Daoqiang Zhang

  • Multimodal Classification of Alzheimer’s Disease and Mild Cognitive Impairment

    Daoqiang Zhang;Yaping Wang;Luping Zhou;Hong Yuan

  • Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation

    Weiling Cai;Songcan Chen;Daoqiang Zhang

  • Multi-modal multi-task learning for joint prediction of multiple regression and classification variables in Alzheimer's disease

    Daoqiang Zhang;Daoqiang Zhang;Dinggang Shen

  • Letters: (2D)2PCA: Two-directional two-dimensional PCA for efficient face representation and recognition

    Daoqiang Zhang;Zhi-Hua Zhou

  • A novel kernelized fuzzy C-means algorithm with application in medical image segmentation

    Dao-Qiang Zhang;Song-Can Chen

  • Identification of MCI individuals using structural and functional connectivity networks

    Chong Yaw Wee;Pew Thian Yap;Daoqiang Zhang;Kevin Denny

  • Semi-Supervised Dimensionality Reduction.

    Daoqiang Zhang;Zhi-Hua Zhou;Songcan Chen

  • Clustering Incomplete Data Using Kernel-Based Fuzzy C-means Algorithm

    Dao-Qiang Zhang;Song-Can Chen

  • Ensemble Sparse Classification of Alzheimer’s Disease

    Manhua Liu;Daoqiang Zhang;Daoqiang Zhang;Dinggang Shen

  • Predicting Future Clinical Changes of MCI Patients Using Longitudinal and Multimodal Biomarkers

    Daoqiang Zhang;Daoqiang Zhang;Dinggang Shen;Alzheimer's Disease Neuroimaging Initiative

  • Constraint Score: A new filter method for feature selection with pairwise constraints

    Daoqiang Zhang;Songcan Chen;Zhi-Hua Zhou

  • A new face recognition method based on SVD perturbation for single example image per person

    Daoqiang Zhang;Songcan Chen;Zhi-Hua Zhou

  • Dual Attention Multi-Instance Deep Learning for Alzheimer’s Disease Diagnosis With Structural MRI

    Wenyong Zhu;Liang Sun;Jiashuang Huang;Liangxiu Han

  • Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification With Chest CT

    Liang Sun;Zhanhao Mo;Fuhua Yan;Liming Xia

  • A Survey on Deep Learning for Neuroimaging-Based Brain Disorder Analysis.

    Li Zhang;Li Zhang;Mingliang Wang;Mingxia Liu;Daoqiang Zhang

  • Relationship Induced Multi-Template Learning for Diagnosis of Alzheimer’s Disease and Mild Cognitive Impairment

    Mingxia Liu;Daoqiang Zhang;Dinggang Shen

  • Domain Transfer Learning for MCI Conversion Prediction

    Bo Cheng;Mingxia Liu;Daoqiang Zhang;Brent C. Munsell

  • Multi-modal Neuroimaging Feature Selection with Consistent Metric Constraint for Diagnosis of Alzheimer’s Disease

    Xiaoke Hao;Yongjin Bao;Yingchun Guo;Ming Yu

  • Group-constrained sparse fMRI connectivity modeling for mild cognitive impairment identification

    Chong Yaw Wee;Pew Thian Yap;Daoqiang Zhang;Daoqiang Zhang;Lihong Wang

  • Enhanced (PC) 2 A for face recognition with one training image per person

    Songcan Chen;Daoqiang Zhang;Zhi-Hua Zhou

  • Rapid and brief communication: Diagonal principal component analysis for face recognition

    Daoqiang Zhang;Zhi-Hua Zhou;Songcan Chen

  • Integration of Network Topological and Connectivity Properties for Neuroimaging Classification

    Biao Jie;Daoqiang Zhang;Wei Gao;Qian Wang

Frequent Co-Authors

Dinggang Shen
Dinggang Shen ShanghaiTech University
Mingxia Liu
Mingxia Liu University of North Carolina at Chapel Hill
Songcan Chen
Songcan Chen Nanjing University of Aeronautics and Astronautics
Jin-Tai Yu
Jin-Tai Yu Fudan University
Zhi-Hua Zhou
Zhi-Hua Zhou Nanjing University
Lan Tan
Lan Tan Qingdao University
Li Shen
Li Shen University of Pennsylvania
Chong Yaw Wee
Chong Yaw Wee University of North Carolina at Chapel Hill
Guorong Wu
Guorong Wu University of North Carolina at Chapel Hill
Pew Thian Yap
Pew Thian Yap University of North Carolina at Chapel Hill

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