World's Best Scientists 2026 revealed!
Yefeng Zheng

Yefeng Zheng

D-Index & Metrics

Computer Science

D-Index
70
Citations
20385
World Ranking
1867
National Ranking
255

Yefeng Zheng 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 Yefeng Zheng 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: 363 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.

Yefeng Zheng 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 Yefeng Zheng 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: 70 D-Index — 87th percentile

87% 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

  • 2018 - Fellow of the Indian National Academy of Engineering (INAE)

Overview

Yefeng Zheng is affiliated with Tencent in China and has an extensive research portfolio encompassing computer science and medicine. Their work primarily focuses on artificial intelligence, computer vision, and biomedical imaging, with significant contributions in subfields such as artificial intelligence, computer vision and pattern recognition, radiology, nuclear medicine and imaging, biomedical engineering, and molecular biology.

Their research covers diverse topics, including:

  • Advanced Neural Network Applications
  • Topic Modeling
  • Domain Adaptation and Few-Shot Learning
  • Radiomics and Machine Learning in Medical Imaging
  • AI in cancer detection
  • COVID-19 diagnosis using AI
  • Medical Image Segmentation Techniques

Zheng has published extensively in venues like arXiv (Cornell University), IEEE Transactions on Medical Imaging, Medical Image Analysis, Proceedings of the AAAI Conference on Artificial Intelligence, and Pattern Recognition. These platforms reflect a consistent engagement with leading journals and conferences in artificial intelligence and medical imaging.

Frequent collaborators include:

  • Kai Ma (118 coauthored works)
  • Yuexiang Li (90 coauthored works)
  • Dong Wei (49 coauthored works)
  • Yawen Huang (45 coauthored works)
  • Donghuan Lu (44 coauthored works)

The scientist's recent papers demonstrate collaborations across domains and address key challenges in medical imaging and AI implementation:

  • The Medical Segmentation Decathlon, 2022, Nature Communications
  • A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging, 2020, Medical Image Analysis
  • Morphological diversity of single neurons in molecularly defined cell types, 2021, Nature
  • Deep Representation-Based Domain Adaptation for Nonstationary EEG Classification, 2020, IEEE Transactions on Neural Networks and Learning Systems
  • Rubik's Cube+: A self-supervised feature learning framework for 3D medical image analysis, 2020, Medical Image Analysis

In addition to journal publications, Zheng has contributed to book chapters published by Springer Science+Business Media. These works primarily focus on medical image computing and computer-assisted intervention, with multiple contributions in the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 book series.

Recognition for their scientific contributions includes being named a Fellow of the Indian National Academy of Engineering (INAE) in 2018.

Best Publications

  • Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

    Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer

  • The Medical Segmentation Decathlon

    Michela Antonelli;Annika Reinke;Spyridon Bakas;Keyvan Farahani

  • Four-Chamber Heart Modeling and Automatic Segmentation for 3-D Cardiac CT Volumes Using Marginal Space Learning and Steerable Features

    Yefeng Zheng;A. Barbu;B. Georgescu;M. Scheuering

  • Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Network

    Zizhao Zhang;Lin Yang;Yefeng Zheng

  • A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging.

    Zhaohan Xiong;Qing Xia;Zhiqiang Hu;Ning Huang

  • Robust point matching for nonrigid shapes by preserving local neighborhood structures

    Yefeng Zheng;D. Doermann

  • Morphological diversity of single neurons in molecularly defined cell types

    Hanchuan Peng;Hanchuan Peng;Peng Xie;Lijuan Liu;Xiuli Kuang

  • Med3D: Transfer Learning for 3D Medical Image Analysis

    Sihong Chen;Kai Ma;Yefeng Zheng

  • Combo loss: Handling input and output imbalance in multi-organ segmentation

    Saeid Asgari Taghanaki;Saeid Asgari Taghanaki;Yefeng Zheng;S. Kevin Zhou;Bogdan Georgescu

  • Multi-Scale Deep Reinforcement Learning for Real-Time 3D-Landmark Detection in CT Scans

    Florin-Cristian Ghesu;Bogdan Georgescu;Yefeng Zheng;Sasa Grbic

  • Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentation

    Yinghuan Shi;Jian Zhang;Tong Ling;Jiwen Lu

  • Script-Independent Text Line Segmentation in Freestyle Handwritten Documents

    Yi Li;Yefeng Zheng;D. Doermann;S. Jaeger

  • Machine printed text and handwriting identification in noisy document images

    Yefeng Zheng;Huiping Li;D. Doermann

  • Deep Representation-Based Domain Adaptation for Nonstationary EEG Classification

    Unknown

  • Calibrated RGB-D Salient Object Detection

    Wei Ji;Jingjing Li;Shuang Yu;Miao Zhang

  • X2CT-GAN: Reconstructing CT From Biplanar X-Rays With Generative Adversarial Networks

    Xingde Ying;Heng Guo;Kai Ma;Jian Wu

  • Fast Automatic Heart Chamber Segmentation from 3D CT Data Using Marginal Space Learning and Steerable Features

    Yefeng Zheng;A. Barbu;B. Georgescu;M. Scheuering

  • PRGC: Potential Relation and Global Correspondence Based Joint Relational Triple Extraction

    Hengyi Zheng;Rui Wen;Xi Chen;Yifan Yang

  • Deep similarity learning for multimodal medical images

    Xi Cheng;Li Zhang;Yefeng Zheng

  • Benchmark for Algorithms Segmenting the Left Atrium From 3D CT and MRI Datasets

    Catalina Tobon-Gomez;Arjan J. Geers;Jochen Peters;Jurgen Weese

  • 3D Deep Learning for Efficient and Robust Landmark Detection in Volumetric Data

    Yefeng Zheng;David Liu;Bogdan Georgescu;Hien Nguyen

  • Hierarchical, learning-based automatic liver segmentation

    Haibin Ling;S.K. Zhou;Yefeng Zheng;B. Georgescu

  • Deep Learning and Convolutional Neural Networks for Medical Image Computing

    Le Lu;Yefeng Zheng;Gustavo Carneiro;Lin Yang

  • Method and system for anatomical object detection using marginal space deep neural networks

    Bogdan Georgescu;Yefeng Zheng;Hien Nguyen;Vivek Kumar Singh

  • Four-Chamber Heart Modeling and Automatic Segmentation for 3D Cardiac CT Volumes

    Yefeng Zheng;Bogdan Georgescu;Adrian Barbu;Michael Scheuering

Frequent Co-Authors

Dorin Comaniciu
Dorin Comaniciu Siemens (United States)
Bogdan Georgescu
Bogdan Georgescu Princeton University
S. Kevin Zhou
S. Kevin Zhou University of Science and Technology of China
David Doermann
David Doermann University at Buffalo, State University of New York
Joachim Hornegger
Joachim Hornegger University of Erlangen-Nuremberg
Linlin Shen
Linlin Shen Shenzhen University
Lin Yang
Lin Yang University of Florida
Andreas Maier
Andreas Maier University of Erlangen-Nuremberg
Deyu Meng
Deyu Meng Xi'an Jiaotong University
Pheng-Ann Heng
Pheng-Ann Heng Chinese University of Hong Kong

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