World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
56
Citations
14427
World Ranking
4026
National Ranking
1919

Pew Thian Yap 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 Pew Thian Yap 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: 395 publications — 87th percentile

87% of scientists in this discipline score the same or lower.

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

Pew Thian Yap 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 Pew Thian Yap 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: 56 D-Index — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

Overview

Pew Thian Yap is affiliated with the University of North Carolina at Chapel Hill in the United States and has contributed extensively to the field of Medicine, with a particular focus on Radiology, Nuclear Medicine, and Imaging.

Their research covers topics including:

  • Advanced MRI Techniques and Applications
  • Advanced Neuroimaging Techniques and Applications
  • Functional Brain Connectivity Studies
  • Medical Image Segmentation Techniques
  • Medical Imaging Techniques and Applications
  • Radiomics and Machine Learning in Medical Imaging
  • Brain Tumor Detection and Classification

Pew Thian Yap has published frequently in several venues, most notably:

  • UNC Libraries
  • Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
  • Lecture notes in computer science
  • arXiv (Cornell University)
  • Medical Image Analysis

Some of their recent papers include:

  • Multi-task learning for segmentation and classification of tumors in 3D automated breast ultrasound images, 2020, Medical Image Analysis
  • Federated learning for medical image analysis: A survey, 2024, Pattern Recognition
  • A Mutual Multi-Scale Triplet Graph Convolutional Network for Classification of Brain Disorders Using Functional or Structural Connectivity, 2021, IEEE Transactions on Medical Imaging
  • Deep Multi-Scale Mesh Feature Learning for Automated Labeling of Raw Dental Surfaces From 3D Intraoral Scanners, 2020, IEEE Transactions on Medical Imaging
  • Multi-site MRI harmonization via attention-guided deep domain adaptation for brain disorder identification, 2021, Medical Image Analysis

The scientist has collaborated frequently with colleagues such as:

  • Dinggang Shen
  • Sahar Ahmad
  • Weili Lin
  • Khoi Minh Huynh
  • Ye Wu

Best Publications

  • Image analysis by Krawtchouk moments

    P.-T. Yap;R. Paramesran;Seng-Huat Ong

  • Infant brain atlases from neonates to 1- and 2-year-olds.

    Feng Shi;Pew Thian Yap;Guorong Wu;Hongjun Jia

  • Identification of MCI individuals using structural and functional connectivity networks

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

  • The UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development.

    Brittany R. Howell;Martin A. Styner;Wei Gao;Wei Gao;Pew-Thian Yap

  • Two-Dimensional Polar Harmonic Transforms for Invariant Image Representation

    Pew-Thian Yap;Xudong Jiang;Alex Chichung Kot

  • LRTV: MR Image Super-Resolution With Low-Rank and Total Variation Regularizations

    Feng Shi;Jian Cheng;Li Wang;Pew-Thian Yap

  • Multi-task learning for segmentation and classification of tumors in 3D automated breast ultrasound images

    Yue Zhou;Houjin Chen;Yanfeng Li;Qin Liu

  • BIRNet: Brain image registration using dual-supervised fully convolutional networks.

    Jingfan Fan;Xiaohuan Cao;Pew Thian Yap;Dinggang Shen;Dinggang Shen

  • Prediction of Alzheimer's disease and mild cognitive impairment using cortical morphological patterns.

    Chong Yaw Wee;Pew Thian Yap;Dinggang Shen

  • Enriched white matter connectivity networks for accurate identification of MCI patients.

    Chong Yaw Wee;Pew Thian Yap;Wenbin Li;Kevin Denny

  • Image Analysis Using Hahn Moments

    Pew-Thian Yap;R. Paramesran;Seng-Huat Ong

  • Development trends of white matter connectivity in the first years of life.

    Pew Thian Yap;Yong Fan;Yasheng Chen;John H. Gilmore

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

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

  • Sparse temporally dynamic resting-state functional connectivity networks for early MCI identification.

    Chong Yaw Wee;Sen Yang;Pew Thian Yap;Dinggang Shen;Dinggang Shen

  • Computational neuroanatomy of baby brains: A review.

    Gang Li;Li Wang;Pew Thian Yap;Fan Wang

  • Image focus measure based on Chebyshev moments

    P.T. Yap;P. Raveendran

  • Anatomical Landmark Based Deep Feature Representation for MR Images in Brain Disease Diagnosis

    Mingxia Liu;Jun Zhang;Dong Nie;Pew-Thian Yap

  • Identifying Autism Spectrum Disorder With Multi-Site fMRI via Low-Rank Domain Adaptation

    Mingliang Wang;Daoqiang Zhang;Jiashuang Huang;Pew-Thian Yap

  • A Mutual Multi-Scale Triplet Graph Convolutional Network for Classification of Brain Disorders Using Functional or Structural Connectivity

    Dongren Yao;Jing Sui;Mingliang Wang;Erkun Yang

  • Altered structural connectivity in neonates at genetic risk for schizophrenia: a combined study using morphological and white matter networks.

    Feng Shi;Pew Thian Yap;Wei Gao;Weili Lin

  • Iterative multi-atlas-based multi-image segmentation with tree-based registration.

    Hongjun Jia;Pew Thian Yap;Dinggang Shen

  • Resting-state multi-spectrum functional connectivity networks for identification of MCI patients.

    Chong Yaw Wee;Pew Thian Yap;Kevin Denny;Jeffrey N. Browndyke

Frequent Co-Authors

Dinggang Shen
Dinggang Shen ShanghaiTech University
Weili Lin
Weili Lin University of North Carolina at Chapel Hill
Guorong Wu
Guorong Wu University of North Carolina at Chapel Hill
Chong Yaw Wee
Chong Yaw Wee University of North Carolina at Chapel Hill
Feng Shi
Feng Shi United Imaging Intelligence (China)
Qian Wang
Qian Wang Shanghai Jiao Tong University
Daoqiang Zhang
Daoqiang Zhang Nanjing University of Aeronautics and Astronautics
Gang Li
Gang Li University of North Carolina at Chapel Hill
Han Zhang
Han Zhang ShanghaiTech University
Lihong Wang
Lihong Wang University of Connecticut Health Center

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