World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
60
Citations
11825
World Ranking
3293
National Ranking
1595

Shuo Li 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 Shuo Li 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: 297 publications — 73rd percentile

73% of scientists in this discipline score the same or lower.

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

Shuo Li 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 Shuo Li 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: 60 D-Index — 78th percentile

78% 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

  • 2025 - School of Engineering Research Award, Case Western Reserve University
  • 2025 - Member, National Academy of Inventors
  • 2025 - SPIE Fellow
  • 2025 - Fellow of the International Academy of Medical and Biological Engineering (IAMBE)
  • 2025 - Fellow of the American Institute for Medical and Biological Engineering (AIMBE)
  • 2025 - Fellow of the American Institute for Medical and Biological Engineering (AIMBE)

Overview

Shuo Li is affiliated with Case Western Reserve University in the United States and has a significant body of research spanning multiple disciplines, primarily in medicine and engineering. Their work encompasses several subfields, including computer vision and pattern recognition, radiology, nuclear medicine and imaging, materials chemistry, electrical and electronic engineering, and biomedical engineering.

The scientist has contributed to key topics such as advanced photocatalysis techniques, radiomics and machine learning in medical imaging, advanced neural network applications, medical image segmentation techniques, medical imaging and analysis, AI in cancer detection, and electrocatalysts for energy conversion.

Frequent collaborators in their research include Heshan Zheng, Yuting He, Guanyu Yang, Yang Chen, and Jo-Shu Chang.

Shuo Li's recent papers include the following:

  • The development of carbon dots: From the perspective of materials chemistry, 2021, Materials Today
  • Recent progress on electrolyte additives for stable lithium metal anode, 2020, Energy Storage Materials
  • Antibiotics degradation by advanced oxidation process (AOPs): Recent advances in ecotoxicity and antibiotic-resistance genes induction of degradation products, 2022, Chemosphere

In addition to journal articles, Shuo Li has contributed to book publications, with two titles published by Springer Science+Business Media in 2020:

  • Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges
  • Computational Methods and Clinical Applications for Spine Imaging

The frequent venues where Shuo Li has published include Medical Image Analysis, IEEE Journal of Biomedical and Health Informatics, arXiv (Cornell University), SSRN Electronic Journal, and Chemical Engineering Journal.

Best Publications

  • Incremental Support Vector Learning for Ordinal Regression

    Bin Gu;Victor S. Sheng;Keng Yeow Tay;Walter Romano

  • Breast Cancer Multi-classification from Histopathological Images with Structured Deep Learning Model.

    Zhongyi Han;Benzheng Wei;Yuanjie Zheng;Yilong Yin

  • Incremental learning for ν -Support Vector Regression

    Bin Gu;Victor S. Sheng;Zhijie Wang;Derek Ho

  • Spine-GAN: Semantic segmentation of multiple spinal structures.

    Zhongyi Han;Benzheng Wei;Ashley Mercado;Stephanie Leung

  • Image Projection Network: 3D to 2D Image Segmentation in OCTA Images

    Mingchao Li;Yerui Chen;Zexuan Ji;Keren Xie

  • Current trends in the development of intelligent unmanned autonomous systems

    Tao Zhang;Qing Li;Chang-shui Zhang;Hua-wei Liang

  • Full left ventricle quantification via deep multitask relationships learning.

    Wufeng Xue;Gary Brahm;Sachin Pandey;Stephanie Leung

  • PM2.5 Data Reliability, Consistency and Air Quality Assessment in Five Chinese Cities†

    Xuan Liang;Shuo Li;Shuyi Zhang;Hui Huang

  • Automated comprehensive Adolescent Idiopathic Scoliosis assessment using MVC-Net

    Hongbo Wu;Chris Bailey;Parham Rasoulinejad;Shuo Li

  • Multi-Target Regression via Robust Low-Rank Learning

    Xiantong Zhen;Mengyang Yu;Xiaofei He;Shuo Li

  • Automatic Landmark Estimation for Adolescent Idiopathic Scoliosis Assessment Using BoostNet

    Hongbo Wu;Chris Bailey;Parham Rasoulinejad;Shuo Li

  • Direct estimation of spinal cobb angles by structured multi-output regression

    Haoliang Sun;Haoliang Sun;Xiantong Zhen;Chris Bailey;Parham Rasoulinejad

  • Multi-scale deep networks and regression forests for direct bi-ventricular volume estimation

    Xiantong Zhen;Zhijie Wang;Ali Islam;Mousumi Bhaduri

  • A multi-center milestone study of clinical vertebral CT segmentation

    Jianhua Yao;Joseph E. Burns;Daniel Forsberg;Alexander Seitel

  • Motion Tracking of the Carotid Artery Wall From Ultrasound Image Sequences: a Nonlinear State-Space Approach

    Zhifan Gao;Yanjie Li;Yuanyuan Sun;Jiayuan Yang

  • An Automatic Cardiac Arrhythmia Classification System With Wearable Electrocardiogram

    Yufa Xia;Huailing Zhang;Lin Xu;Zhifan Gao

  • Direct delineation of myocardial infarction without contrast agents using a joint motion feature learning architecture.

    Chenchu Xu;Chenchu Xu;Lei Xu;Zhifan Gao;Shen Zhao

  • Multi-modal vertebrae recognition using Transformed Deep Convolution Network.

    Yunliang Cai;Mark Landis;David T. Laidley;Anat Kornecki

  • Coarse-to-fine classification for diabetic retinopathy grading using convolutional neural network.

    Zhan Wu;Gonglei Shi;Yang Chen;Fei Shi

  • Embedding Overlap Priors in Variational Left Ventricle Tracking

    I. Ben Ayed;Shuo Li;I. Ross

  • Regional Assessment of Cardiac Left Ventricular Myocardial Function via MRI Statistical Features

    Mariam Afshin;Ismail Ben Ayed;Kumaradevan Punithakumar;Max Law

Frequent Co-Authors

Heye Zhang
Heye Zhang Sun Yat-sen University
Ismail Ben Ayed
Ismail Ben Ayed École de Technologie Supérieure
Xiantong Zhen
Xiantong Zhen University of Amsterdam
Robert F. Shepherd
Robert F. Shepherd Cornell University
Terry M. Peters
Terry M. Peters University of Western Ontario
Adam Krzyżak
Adam Krzyżak Concordia University
Guoyan Zheng
Guoyan Zheng Shanghai Jiao Tong University
Yilong Yin
Yilong Yin Shandong University
Kuanquan Wang
Kuanquan Wang Harbin Institute of Technology
Huazhong Shu
Huazhong Shu Southeast University

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