World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
61
Citations
12685
World Ranking
3117
National Ranking
54

Xin Yuan 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 Xin Yuan 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: 345 publications — 81st percentile

81% of scientists in this discipline score the same or lower.

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

Xin Yuan 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 Xin Yuan 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: 61 D-Index — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Overview

Xin Yuan is affiliated with Nanyang Technological University in Singapore and has contributed extensively to research in engineering and computer science domains. Their work predominantly centers on computational imaging, signal processing, and related technological applications.

Their research focuses on key areas including sparse and compressive sensing techniques, photoacoustic and ultrasonic imaging, image and signal denoising methods, advanced image processing techniques, medical imaging techniques and applications, advanced image fusion techniques, and advanced MRI techniques and applications.

Xin Yuan has authored influential papers, such as:

  • Snapshot Compressive Imaging: Theory, Algorithms, and Applications (2021, IEEE Signal Processing Magazine)
  • Mask-guided Spectral-wise Transformer for Efficient Hyperspectral Image Reconstruction (2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition)
  • Deep learning for video compressive sensing (2020, APL Photonics)
  • HDNet: High-resolution Dual-domain Learning for Spectral Compressive Imaging (2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition)
  • Image Restoration via Simultaneous Nonlocal Self-Similarity Priors (2020, IEEE Transactions on Image Processing)

Frequent co-authors collaborating with Xin Yuan include:

  • Yulun Zhang
  • Ziyi Meng
  • Ce Zhu
  • Zhiyuan Zha
  • Bihan Wen

Xin Yuan's research has been published regularly in notable venues, including:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Optics Letters
  • IEEE Transactions on Image Processing
  • IEEE Transactions on Pattern Analysis and Machine Intelligence

The scientist's work engages deeply with computer vision and pattern recognition, biomedical engineering, computational mechanics, radiology, nuclear medicine and imaging, and media technology, reflecting interdisciplinary approaches to advanced imaging and computational methodologies.

Best Publications

  • Variational autoencoder for deep learning of images, labels and captions

    Yunchen Pu;Zhe Gan;Ricardo Henao;Xin Yuan

  • Coded aperture compressive temporal imaging

    Patrick Llull;Xuejun Liao;Xin Yuan;Jianbo Yang

  • Rank Minimization for Snapshot Compressive Imaging

    Yang Liu;Xin Yuan;Jinli Suo;David J. Brady

  • Mask-guided Spectral-wise Transformer for Efficient Hyperspectral Image Reconstruction

    Unknown

  • Generalized alternating projection based total variation minimization for compressive sensing

    Xin Yuan

  • Snapshot Compressive Imaging: Principle, Implementation, Theory, Algorithms and Applications.

    Xin Yuan;David J. Brady;Aggelos K. Katsaggelos

  • Hyperspectral Image Spatial Super-Resolution via 3D Full Convolutional Neural Network

    Shaohui Mei;Xin Yuan;Jingyu Ji;Yifan Zhang

  • Variational Autoencoder for Deep Learning of Images, Labels and Captions

    Yunchen Pu;Zhe Gan;Ricardo Henao;Xin Yuan

  • Computational Snapshot Multispectral Cameras: Toward dynamic capture of the spectral world

    Xun Cao;Tao Yue;Xing Lin;Stephen Lin

  • HDNet: High-resolution Dual-domain Learning for Spectral Compressive Imaging

    Unknown

  • Video compressive sensing using Gaussian mixture models.

    Jianbo Yang;Xin Yuan;Xuejun Liao;Patrick Llull

  • Compressive Sensing by Learning a Gaussian Mixture Model From Measurements

    Jianbo Yang;Xuejun Liao;Xin Yuan;Patrick Llull

  • Compressive Hyperspectral Imaging With Side Information

    Xin Yuan;Tsung-Han Tsai;Ruoyu Zhu;Patrick Llull

  • lambda-Net: Reconstruct Hyperspectral Images From a Snapshot Measurement

    Xin Miao;Xin Yuan;Yunchen Pu;Vassilis Athitsos

  • Plug-and-Play Algorithms for Large-Scale Snapshot Compressive Imaging

    Xin Yuan;Yang Liu;Jinli Suo;Qionghai Dai

  • End-to-End Low Cost Compressive Spectral Imaging with Spatial-Spectral Self-Attention

    Ziyi Meng;Jiawei Ma;Xin Yuan

  • “Vector Cross-Product Direction-Finding” With an Electromagnetic Vector-Sensor of Six Orthogonally Oriented But Spatially Noncollocating Dipoles/Loops

    Kainam Thomas Wong;Xin Yuan

  • Deep Tensor ADMM-Net for Snapshot Compressive Imaging

    Jiawei Ma;Xiao-Yang Liu;Zheng Shou;Xin Yuan

  • Deep learning for video compressive sensing

    Mu Qiao;Ziyi Meng;Ziyi Meng;Jiawei Ma;Xin Yuan

  • Deep Gaussian Scale Mixture Prior for Spectral Compressive Imaging

    Tao Huang;Weisheng Dong;Xin Yuan;Jinjian Wu

  • Image Restoration via Simultaneous Nonlocal Self-Similarity Priors

    Zhiyuan Zha;Xin Yuan;Jiantao Zhou;Ce Zhu

  • Low-Cost Compressive Sensing for Color Video and Depth

    Xin Yuan;Patrick Llull;Xuejun Liao;Jianbo Yang

  • Spectral-temporal compressive imaging

    Tsung Han Tsai;Patrick Llull;Xin Yuan;Lawrence Carin

Frequent Co-Authors

Lawrence Carin
Lawrence Carin Duke University
David J. Brady
David J. Brady University of Arizona
Bihan Wen
Bihan Wen Nanyang Technological University
Ce Zhu
Ce Zhu University of Electronic Science and Technology of China
Jiantao Zhou
Jiantao Zhou University of Macau
Guillermo Sapiro
Guillermo Sapiro Princeton University
Qionghai Dai
Qionghai Dai Tsinghua University
Jinli Suo
Jinli Suo Tsinghua University
Christopher H. T. Lee
Christopher H. T. Lee Nanyang Technological University
Bo Chen
Bo Chen Xidian University

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