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D-Index & Metrics

Computer Science

D-Index
37
Citations
6263
World Ranking
10693
National Ranking
4471

Leslie Ying 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 Leslie Ying 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: 211 publications — 50th percentile

50% of scientists in this discipline score the same or lower.

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

Leslie Ying 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 Leslie Ying 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: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Leslie Ying is affiliated with the University at Buffalo, State University of New York in the United States. Their research primarily focuses on Medicine, with a significant emphasis on Radiology, Nuclear Medicine and Imaging. Their work also spans Biomedical Engineering, Computer Vision and Pattern Recognition, Biophysics, and Computational Mechanics.

The scientist's major areas of study include Advanced MRI Techniques and Applications, Medical Imaging Techniques and Applications, Advanced Neuroimaging Techniques and Applications, Radiomics and Machine Learning in Medical Imaging, Wireless Body Area Networks, Photoacoustic and Ultrasonic Imaging, and MRI in cancer diagnosis.

Recent publications by Leslie Ying feature the following works:

  • Deep Magnetic Resonance Image Reconstruction: Inverse Problems Meet Neural Networks, 2020, IEEE Signal Processing Magazine
  • DeepcomplexMRI: Exploiting deep residual network for fast parallel MR imaging with complex convolution, 2020, Magnetic Resonance Imaging
  • Deep low-Rank plus sparse network for dynamic MR imaging, 2021, Medical Image Analysis
  • Learned Low-Rank Priors in Dynamic MR Imaging, 2021, IEEE Transactions on Medical Imaging
  • A New Deep Learning Network for Mitigating Limited-view and Under-sampling Artifacts in Ring-shaped Photoacoustic Tomography, 2020, Computerized Medical Imaging and Graphics

Frequent publication venues for Leslie Ying include:

  • 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
  • IEEE Transactions on Medical Imaging
  • arXiv (Cornell University)
  • IEEE Signal Processing Magazine
  • Magnetic Resonance in Medicine

Leslie Ying collaborates often with researchers including Dong Liang, Xiaoliang Zhang, Peizhou Huang, Yanjie Zhu, and Xiaojuan Li.

Best Publications

  • Accelerating magnetic resonance imaging via deep learning

    Shanshan Wang;Zhenghang Su;Leslie Ying;Xi Peng

  • Accelerating SENSE using compressed sensing.

    Dong Liang;Bo Liu;Bo Liu;JiunJie Wang;Leslie Ying

  • Deep Magnetic Resonance Image Reconstruction: Inverse Problems Meet Neural Networks

    Dong Liang;Jing Cheng;Ziwen Ke;Leslie Ying

  • Joint image reconstruction and sensitivity estimation in SENSE (JSENSE).

    Leslie Ying;Jinhua Sheng

  • DeepcomplexMRI: Exploiting deep residual network for fast parallel MR imaging with complex convolution

    Shanshan Wang;Huitao Cheng;Leslie Ying;Taohui Xiao

  • Beamlet Transform‐Based Technique for Pavement Crack Detection and Classification

    Leslie Ying;Ezzatollah Salari

  • Compressed Sensing Dynamic Cardiac Cine MRI Using Learned Spatiotemporal Dictionary

    Yanhua Wang;Leslie Ying

  • DIMENSION: Dynamic MR imaging with both k‐space and spatial prior knowledge obtained via multi‐supervised network training

    Shanshan Wang;Ziwen Ke;Huitao Cheng;Sen Jia

  • Regularized sensitivity encoding (SENSE) reconstruction using bregman iterations

    Bo Liu;Kevin King;Michael Steckner;Jun Xie

  • Adaptive Dictionary Learning in Sparse Gradient Domain for Image Recovery

    Qiegen Liu;Shanshan Wang;Leslie Ying;Xi Peng

  • k-t ISD: Dynamic cardiac MR imaging using compressed sensing with iterative support detection

    Dong Liang;Edward V R DiBella;Rong Rong Chen;Leslie Ying

  • On Tikhonov regularization for image reconstruction in parallel MRI

    L. Ying;D. Xu;Z.-P. Liang

  • Nonlinear GRAPPA: A kernel approach to parallel MRI reconstruction

    Yuchou Chang;Dong Liang;Leslie Ying

  • Sensitivity encoding reconstruction with nonlocal total variation regularization.

    Dong Liang;Haifeng Wang;Yuchou Chang;Leslie Ying

  • Sparsesense: Application of compressed sensing in parallel MRI

    Bo Liu;Yi Ming Zou;L. Ying

  • Compressed-sensing photoacoustic computed tomography in vivo with partially known support

    Jing Meng;Lihong V. Wang;Leslie Ying;Dong Liang

  • A Kernel-Based Low-Rank (KLR) Model for Low-Dimensional Manifold Recovery in Highly Accelerated Dynamic MRI

    Ukash Nakarmi;Yanhua Wang;Jingyuan Lyu;Dong Liang

  • Parallel MRI Using Phased Array Coils

    Leslie Ying;Zhi-Pei Liang

  • Deep low-Rank plus sparse network for dynamic MR imaging.

    Wenqi Huang;Ziwen Ke;Zhuo-Xu Cui;Jing Cheng

  • Learning Joint-Sparse Codes for Calibration-Free Parallel MR Imaging

    Shanshan Wang;Sha Tan;Yuan Gao;Qiegen Liu

  • Toeplitz block matrices in compressed sensing and their applications in imaging

    F. Sebert;Yi Ming Zou;L. Ying

  • DeepcomplexMRI: Exploiting deep residual network for fast parallel MR imaging with complex convolution

    Shanshan Wang;Huitao Cheng;Leslie Ying;Taohui Xiao

Frequent Co-Authors

Dong Liang
Dong Liang Chinese Academy of Sciences
Hairong Zheng
Hairong Zheng Chinese Academy of Sciences
Xin Liu
Xin Liu Chinese Academy of Sciences
Zhi-Pei Liang
Zhi-Pei Liang University of Illinois at Urbana-Champaign
Xi Peng
Xi Peng Sichuan University
Gesualdo Scutari
Gesualdo Scutari Purdue University West Lafayette
Dong Xu
Dong Xu University of Missouri
Jun Xia
Jun Xia University at Buffalo, State University of New York
Ying-Zu Huang
Ying-Zu Huang Chang Gung University
Song-Hai Shi
Song-Hai Shi Tsinghua University

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