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Ziyue Xu

D-Index & Metrics

Computer Science

D-Index
38
Citations
12142
World Ranking
9966
National Ranking
4194

Ziyue Xu 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 Ziyue Xu 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: 146 publications — 25th percentile

25% of scientists in this discipline score the same or lower.

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

Ziyue Xu 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 Ziyue Xu 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: 38 D-Index — 30th percentile

30% of scientists in this discipline score the same or lower.

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

Overview

Ziyue Xu is affiliated with Nvidia in the United States and has a prolific academic record spanning multiple areas within computer science and medicine. Their research primarily explores the intersection of artificial intelligence and medical imaging, focusing on topics such as radiomics, machine learning, and applications of AI in disease diagnosis and treatment.

They have published extensively, with key recent papers including:

  • Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets (2020, Nature Communications)
  • Generalizing Deep Learning for Medical Image Segmentation to Unseen Domains via Deep Stacked Transformation (2020, IEEE Transactions on Medical Imaging)
  • When Radiology Report Generation Meets Knowledge Graph (2020, Proceedings of the AAAI Conference on Artificial Intelligence)
  • Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japan (2021, Medical Image Analysis)
  • Federated learning improves site performance in multicenter deep learning without data sharing (2020, Journal of the American Medical Informatics Association)

Xu collaborates frequently with several researchers, including:

  • Daguang Xu (59 joint publications)
  • Holger R. Roth (39 joint publications)
  • Dong Yang (37 joint publications)
  • Bradford J. Wood (26 joint publications)
  • Barış Türkbey (26 joint publications)

Their publications are commonly found in notable venues such as:

  • arXiv (Cornell University) with 25 publications
  • Medical Image Analysis with 3 publications
  • Academic Radiology with 3 publications
  • Abdominal Radiology with 3 publications
  • The Journal of Urology with 3 publications

Xu has contributed chapters to several books published by Springer Science+Business Media, including works on domain adaptation, representation transfer, distributed and collaborative learning, and applications of AI in affordable healthcare and global health.

Their main fields of study include computer science with 108 publications and medicine with 91 publications. Subfields of particular focus comprise:

  • Artificial Intelligence (55 publications)
  • Computer Vision and Pattern Recognition (52 publications)
  • Radiology, Nuclear Medicine and Imaging (51 publications)
  • Pulmonary and Respiratory Medicine (24 publications)
  • Molecular Biology (12 publications)

The primary research topics pursued by Xu are:

  • Radiomics and Machine Learning in Medical Imaging (54 publications)
  • Advanced Neural Network Applications (40 publications)
  • COVID-19 Diagnosis Using AI (36 publications)
  • AI in Cancer Detection (28 publications)
  • Prostate Cancer Diagnosis and Treatment (26 publications)
  • Privacy-Preserving Technologies in Data (24 publications)
  • Medical Image Segmentation Techniques (24 publications)

Best Publications

  • Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

    Hoo-Chang Shin;Holger R. Roth;Mingchen Gao;Le Lu

  • Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets.

    Stephanie A. Harmon;Thomas H. Sanford;Sheng Xu;Evrim B. Turkbey

  • Generalizing Deep Learning for Medical Image Segmentation to Unseen Domains via Deep Stacked Transformation

    Ling Zhang;Xiaosong Wang;Dong Yang;Thomas Sanford

  • A review on segmentation of positron emission tomography images

    Brent Foster;Ulas Bagci;Awais Mansoor;Ziyue Xu

  • Segmentation and Image Analysis of Abnormal Lungs at CT: Current Approaches, Challenges, and Future Trends

    Awais Mansoor;Ulas Bagci;Brent Foster;Ziyue Xu

  • Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge

    Hugo J. Kuijf;Adria Casamitjana;D. Louis Collins;Mahsa Dadar

  • Holistic classification of CT attenuation patterns for interstitial lung diseases via deep convolutional neural networks.

    Mingchen Gao;Ulas Bagci;Le Lu;Aaron Wu

  • When Radiology Report Generation Meets Knowledge Graph

    Yixiao Zhang;Xiaosong Wang;Ziyue Xu;Qihang Yu

  • Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japan.

    Dong Yang;Ziyue Xu;Wenqi Li;Andriy Myronenko

  • Federated learning improves site performance in multicenter deep learning without data sharing.

    Karthik V Sarma;Stephanie Harmon;Thomas Sanford;Holger R Roth

  • A Generic Approach to Pathological Lung Segmentation

    Awais Mansoor;Ulas Bagci;Ziyue Xu;Brent Foster

  • Joint segmentation of anatomical and functional images: Applications in quantification of lesions from PET, PET-CT, MRI-PET, and MRI-PET-CT images

    Ulas Bagci;Jayaram K. Udupa;Neil Mendhiratta;Neil Mendhiratta;Brent Foster

  • CT-Realistic Lung Nodule Simulation from 3D Conditional Generative Adversarial Networks for Robust Lung Segmentation

    Dakai Jin;Ziyue Xu;Youbao Tang;Adam P. Harrison

  • Progressive and Multi-path Holistically Nested Neural Networks for Pathological Lung Segmentation from CT Images

    Adam P. Harrison;Ziyue Xu;Kevin George;Le Lu

  • Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge

    Hugo J. Kuijf;J. Matthijs Biesbroek;Jeroen de Bresser;Rutger Heinen

  • Deep vessel tracking: A generalized probabilistic approach via deep learning

    Aaron Wu;Ziyue Xu;Mingchen Gao;Mario Buty

  • Capsules for biomedical image segmentation.

    Rodney LaLonde;Ziyue Xu;Ismail Irmakci;Sanjay Jain

  • Closing the Generalization Gap of Cross-silo Federated Medical Image Segmentation

    Unknown

  • Segmentation of PET Images for Computer-Aided Functional Quantification of Tuberculosis in Small Animal Models

    Brent Foster;Ulas Bagci;Ziyue Xu;Bappaditya Dey

  • Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data

    Unknown

  • 3D Convolutional Neural Networks with Graph Refinement for Airway Segmentation Using Incomplete Data Labels

    Dakai Jin;Ziyue Xu;Adam P. Harrison;Kevin George

  • A Cascaded Deep Learning-Based Artificial Intelligence Algorithm for Automated Lesion Detection and Classification on Biparametric Prostate Magnetic Resonance Imaging.

    Sherif Mehralivand;Dong Yang;Stephanie A. Harmon;Daguang Xu

  • Determination of disease severity in COVID-19 patients using deep learning in chest X-ray images.

    Maxime Blain;Michael T. Kassin;Nicole Varble;Xiaosong Wang

  • Interactive segmentation of medical images through fully convolutional neural networks.

    Tomas Sakinis;Fausto Milletari;Holger Roth;Panagiotis Korfiatis

Frequent Co-Authors

Daguang Xu
Daguang Xu Nvidia (United Kingdom)
Holger R. Roth
Holger R. Roth Nvidia (United States)
Ulas Bagci
Ulas Bagci Northwestern University
Baris Turkbey
Baris Turkbey National Institutes of Health
Ronald M. Summers
Ronald M. Summers National Institutes of Health
Le Lu
Le Lu Alibaba Group (China)
Bradford J. Wood
Bradford J. Wood National Institutes of Health
Jayaram K. Udupa
Jayaram K. Udupa University of Pennsylvania
Peter L. Choyke
Peter L. Choyke National Institutes of Health
William R. Bishai
William R. Bishai Johns Hopkins University

External Links

Personal website of Ziyue Xu

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Best Scientists Citing Ziyue Xu

Le Lu

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