World's Best Scientists 2026 revealed!

D-Index & Metrics

Neuroscience

D-Index
37
Citations
5501
World Ranking
8802
National Ranking
136

Kaiming Li publication distribution in Neuroscience in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Neuroscience in 2026. The highlighted bar marks where Kaiming Li sits on this spectrum.

38–47 publications: 18 scientists 48–57 publications: 79 scientists 58–67 publications: 193 scientists 68–77 publications: 323 scientists 78–87 publications: 406 scientists 88–97 publications: 452 scientists 98–107 publications: 539 scientists 108–117 publications: 505 scientists 118–127 publications: 522 scientists 128–137 publications: 469 scientists 138–147 publications: 456 scientists 148–157 publications: 459 scientists 158–167 publications: 397 scientists 168–177 publications: 383 scientists 178–187 publications: 350 scientists 188–197 publications: 302 scientists 198–207 publications: 306 scientists 208–217 publications: 262 scientists 218–227 publications: 242 scientists 228–237 publications: 220 scientists 238–247 publications: 203 scientists 248–257 publications: 174 scientists 258–267 publications: 176 scientists 268–277 publications: 175 scientists 278–287 publications: 125 scientists 288–297 publications: 116 scientists 298–307 publications: 127 scientists 308–317 publications: 128 scientists 318–327 publications: 99 scientists 328–337 publications: 89 scientists 338–347 publications: 78 scientists 348–357 publications: 96 scientists 358–367 publications: 66 scientists 368–377 publications: 59 scientists 378–387 publications: 65 scientists 388–397 publications: 54 scientists 398–407 publications: 48 scientists 408–417 publications: 49 scientists 418–427 publications: 34 scientists 428–437 publications: 31 scientists 438–447 publications: 30 scientists 448–457 publications: 31 scientists 458–467 publications: 36 scientists 468–477 publications: 40 scientists 478–487 publications: 35 scientists 488–497 publications: 30 scientists 498–507 publications: 23 scientists 508–517 publications: 26 scientists 518–527 publications: 20 scientists 528–537 publications: 23 scientists 538–547 publications: 20 scientists 548–557 publications: 20 scientists 558–567 publications: 17 scientists 568–577 publications: 14 scientists 578–587 publications: 20 scientists 588–597 publications: 20 scientists 598–607 publications: 19 scientists 608–617 publications: 18 scientists 618–627 publications: 17 scientists 628–637 publications: 11 scientists 638–647 publications: 11 scientists 648–657 publications: 11 scientists 658–667 publications: 8 scientists 668–677 publications: 7 scientists 678–687 publications: 11 scientists 688–697 publications: 10 scientists 698–707 publications: 4 scientists 708–717 publications: 6 scientists 718–727 publications: 5 scientists 728–737 publications: 5 scientists 738–747 publications: 9 scientists 748–757 publications: 9 scientists 758–767 publications: 3 scientists 768–777 publications: 7 scientists 778–787 publications: 7 scientists 788–797 publications: 6 scientists 798–807 publications: 2 scientists 808–817 publications: 2 scientists 818–827 publications: 7 scientists 828–837 publications: 0 scientists 838–847 publications: 9 scientists 848–857 publications: 3 scientists 858–867 publications: 1 scientists 868–877 publications: 3 scientists 878–886 publications: 6 scientists 887+ publications: 100 scientists
38 publications 887+

This scientist: 101 publications — 17th percentile

17% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 887 publications or more.

Kaiming Li D-index placement in Neuroscience in 2026

The chart shows the D-index (discipline H-index) distribution of Neuroscience scientists ranked by Research.com in 2026. The highlighted bar marks where Kaiming Li sits on this spectrum.

30–31 D-Index: 42 scientists 32–33 D-Index: 172 scientists 34–35 D-Index: 296 scientists 36–37 D-Index: 435 scientists 38–39 D-Index: 459 scientists 40–41 D-Index: 456 scientists 42–43 D-Index: 467 scientists 44–45 D-Index: 478 scientists 46–47 D-Index: 512 scientists 48–49 D-Index: 435 scientists 50–51 D-Index: 425 scientists 52–53 D-Index: 418 scientists 54–55 D-Index: 392 scientists 56–57 D-Index: 357 scientists 58–59 D-Index: 334 scientists 60–61 D-Index: 328 scientists 62–63 D-Index: 260 scientists 64–65 D-Index: 278 scientists 66–67 D-Index: 239 scientists 68–69 D-Index: 250 scientists 70–71 D-Index: 210 scientists 72–73 D-Index: 200 scientists 74–75 D-Index: 189 scientists 76–77 D-Index: 170 scientists 78–79 D-Index: 146 scientists 80–81 D-Index: 113 scientists 82–83 D-Index: 126 scientists 84–85 D-Index: 100 scientists 86–87 D-Index: 84 scientists 88–89 D-Index: 99 scientists 90–91 D-Index: 84 scientists 92–93 D-Index: 85 scientists 94–95 D-Index: 72 scientists 96–97 D-Index: 76 scientists 98–99 D-Index: 45 scientists 100–101 D-Index: 49 scientists 102–103 D-Index: 43 scientists 104–105 D-Index: 32 scientists 106–107 D-Index: 45 scientists 108–109 D-Index: 50 scientists 110–111 D-Index: 32 scientists 112–113 D-Index: 39 scientists 114–115 D-Index: 32 scientists 116–117 D-Index: 29 scientists 118–119 D-Index: 27 scientists 120–121 D-Index: 19 scientists 122–123 D-Index: 23 scientists 124–125 D-Index: 27 scientists 126–127 D-Index: 16 scientists 128–129 D-Index: 24 scientists 130–131 D-Index: 13 scientists 132–133 D-Index: 21 scientists 134–135 D-Index: 17 scientists 136–137 D-Index: 14 scientists 138–139 D-Index: 15 scientists 140–141 D-Index: 10 scientists 142–143 D-Index: 10 scientists 144–145 D-Index: 13 scientists 146–147 D-Index: 9 scientists 148–149 D-Index: 8 scientists 150–151 D-Index: 6 scientists 152–153 D-Index: 6 scientists 154–155 D-Index: 7 scientists 156–157 D-Index: 7 scientists 158–159 D-Index: 10 scientists 160–161 D-Index: 4 scientists 162 D-Index: 8 scientists 163+ D-Index: 100 scientists
30 D-Index 163+

This scientist: 37 D-Index — 10th percentile

10% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 163 D-Index or more.

Overview

Kaiming Li is affiliated with Sichuan University in China and has contributed extensively to the field of engineering, with a primary focus on aerospace, electrical and electronic, and biomedical engineering. Their publication record includes significant work in areas such as advanced synthetic aperture radar (SAR) imaging techniques, radar systems and signal processing, and advancements in battery materials and technologies.

The scientist has published papers in a variety of journals and conferences, frequently appearing in venues such as Remote Sensing, IEEE Sensors Journal, IEEE Transactions on Aerospace and Electronic Systems, IEEE Geoscience and Remote Sensing Letters, and the Journal of Power Electronics.

Their research topics encompass:

  • Advanced SAR Imaging Techniques
  • Radar Systems and Signal Processing
  • Sparse and Compressive Sensing Techniques
  • Advanced Battery Materials and Technologies
  • Advancements in Battery Materials
  • Microwave Imaging and Scattering Analysis
  • Underwater Acoustics Research

Some of the recent publications include:

  • "Gas-Sensing Performances of Metal Oxide Nanostructures for Detecting Dissolved Gases: A Mini Review," 2020, Frontiers in Chemistry
  • "Low-Cost Gel Polymer Electrolyte for High-Performance Aluminum-Ion Batteries," 2021, ACS Applied Materials & Interfaces
  • "Robust lithium storage of block copolymer-templated mesoporous TiNb2O7 and TiNb2O7@C anodes evaluated in half-cell and full-battery configurations," 2021, Electrochimica Acta
  • "A reliable gel polymer electrolyte enables stable cycling of rechargeable aluminum batteries in a wide-temperature range," 2021, Journal of Power Sources
  • "Experimental study and multi-objective optimization for drip irrigation of grapes in arid areas of northwest China," 2020, Agricultural Water Management

Kaiming Li frequently collaborates with several researchers, including Qun Zhang, Ying Luo, Huan Wang, Yuanpeng Zhang, and Haobo Wang, with multiple joint publications reflecting sustained academic partnerships.

Best Publications

  • Reduced default mode network functional connectivity in patients with recurrent major depressive disorder.

    Chao-Gan Yan;Xiao Chen;Le Li;Francisco Xavier Castellanos

  • An open science resource for establishing reliability and reproducibility in functional connectomics

    Xi Nian Zuo;Jeffrey S. Anderson;Pierre Bellec;Rasmus M. Birn

  • Review of methods for functional brain connectivity detection using fMRI

    Kaiming Li;Lei Guo;Jingxin Nie;Gang Li

  • Disrupted intrinsic functional brain topology in patients with major depressive disorder.

    Hong Yang;Xiao Chen;Zuo Bing Chen;Le Li

  • Representing and Retrieving Video Shots in Human-Centric Brain Imaging Space

    Junwei Han;Xiang Ji;Xintao Hu;Dajiang Zhu

  • DICCCOL: Dense Individualized and Common Connectivity-Based Cortical Landmarks

    Dajiang Zhu;Kaiming Li;Kaiming Li;Lei Guo;Xi Jiang

  • Disrupted brain network topology in pediatric posttraumatic stress disorder: A resting-state fMRI study.

    Xueling Suo;Du Lei;Kaiming Li;Fuqin Chen

  • Disrupted Functional Brain Connectome in Patients with Posttraumatic Stress Disorder.

    Du Lei;Kaiming Li;Lingjiang Li;Fuqin Chen

  • Microstructural brain abnormalities in medication-free patients with major depressive disorder: a systematic review and meta-analysis of diffusion tensor imaging.

    Jing Jiang;You-Jin Zhao;Xin-Yu Hu;Ming-Ying Du

  • Axonal Fiber Terminations Concentrate on Gyri

    Jingxin Nie;Lei Guo;Kaiming Li;Kaiming Li;Yonghua Wang

  • Altered resting-state dynamic functional brain networks in major depressive disorder: Findings from the REST-meta-MDD consortium

    Yicheng Long;Hengyi Cao;Chaogan Yan;Xiao Chen

  • Complex span tasks and hippocampal recruitment during working memory

    Carlos Cesar Faraco;Nash Unsworth;Jason Langley;Doug Terry

  • Biotypes of major depressive disorder: Neuroimaging evidence from resting-state default mode network patterns.

    Sugai Liang;Wei Deng;Xiaojing Li;Andrew J. Greenshaw

  • Predicting Functional Cortical ROIs via DTI-Derived Fiber Shape Models

    Tuo Zhang;Lei Guo;Kaiming Li;Kaiming Li;Changfeng Jing

  • Connectome-scale assessments of structural and functional connectivity in MCI.

    Dajiang Zhu;Kaiming Li;Douglas P. Terry;A. Nicholas Puente

  • Coevolution of Gyral Folding and Structural Connection Patterns in Primate Brains

    Hanbo Chen;Tuo Zhang;Tuo Zhang;Lei Guo;Kaiming Li;Kaiming Li

  • Characterization of U-shape streamline fibers: Methods and applications

    Tuo Zhang;Hanbo Chen;Lei Guo;Kaiming Li

  • Optimization of functional brain ROIs via maximization of consistency of structural connectivity profiles

    Dajiang Zhu;Kaiming Li;Kaiming Li;Carlos Cesar Faraco;Fan Deng

  • Graph convolutional network for fMRI analysis based on connectivity neighborhood.

    Lebo Wang;Kaiming Li;Xiaoping P Hu

  • Gyral folding pattern analysis via surface profiling.

    Kaiming Li;Lei Guo;Gang Li;Jingxin Nie

  • An open science resource for establishing reliability and reproducibility in functional

    Randy L. Buckner;Vince D. Calhoun;F. Xavier Castellanos;Antao Chen

Frequent Co-Authors

Tianming Liu
Tianming Liu University of Georgia
Lei Guo
Lei Guo Beijing University of Posts and Telecommunications
Qiyong Gong
Qiyong Gong Sichuan University
Jiang Qiu
Jiang Qiu Southwest University
L. Stephen Miller
L. Stephen Miller University of Georgia
Gang Li
Gang Li University of North Carolina at Chapel Hill
Yu-Feng Zang
Yu-Feng Zang Hangzhou Normal University
Chao-Gan Yan
Chao-Gan Yan Tsinghua University
Xi-Nian Zuo
Xi-Nian Zuo Beijing Normal University
Wenbin Guo
Wenbin Guo Central South University

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