World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
35
Citations
3942
World Ranking
11836
National Ranking
1473

Zhenghui Gu 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 Zhenghui Gu 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: 145 publications — 25th percentile

25% of scientists in this discipline score the same or lower.

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

Zhenghui Gu 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 Zhenghui Gu 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: 35 D-Index — 20th percentile

20% of scientists in this discipline score the same or lower.

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

Overview

Zhenghui Gu is affiliated with South China University of Technology in China. Their research predominantly focuses on neuroscience and engineering, bringing together interdisciplinary knowledge from these fields.

The main fields of study covered in their work include:

  • Neuroscience
  • Engineering

Within these areas, Gu has contributed to several subfields such as:

  • Cognitive Neuroscience
  • Electrical and Electronic Engineering
  • Signal Processing
  • Cellular and Molecular Neuroscience
  • Computer Vision and Pattern Recognition

Their research topics demonstrate a focus on:

  • EEG and Brain-Computer Interfaces
  • Advanced Memory and Neural Computing
  • Neuroscience and Neural Engineering
  • Blind Source Separation Techniques
  • Sparse and Compressive Sensing Techniques
  • Neural dynamics and brain function
  • Advanced MRI Techniques and Applications

Gu has several recent publications that reflect their research areas. Selected works include:

  • "Deep Temporal-Spatial Feature Learning for Motor Imagery-Based Brain-Computer Interfaces" (2020), published in IEEE Transactions on Neural Systems and Rehabilitation Engineering
  • "Spatiotemporal-Filtering-Based Channel Selection for Single-Trial EEG Classification" (2020), published in IEEE Transactions on Cybernetics
  • "A Bayesian Shared Control Approach for Wheelchair Robot With Brain Machine Interface" (2020), published in IEEE Transactions on Neural Systems and Rehabilitation Engineering
  • "Capsule Network for ERP Detection in Brain-Computer Interface" (2021), published in IEEE Transactions on Neural Systems and Rehabilitation Engineering
  • "A Multi-Domain Convolutional Neural Network for EEG-Based Motor Imagery Decoding" (2023), published in IEEE Transactions on Neural Systems and Rehabilitation Engineering

Gu frequently publishes in the following venues:

  • IEEE Transactions on Neural Systems and Rehabilitation Engineering
  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • IEEE Transactions on Biomedical Engineering
  • Neurocomputing

Collaboration is notable in Gu's work, with several frequent co-authors:

  • Yuanqing Li
  • Zhu Liang Yu
  • Tianyou Yu
  • Zhuliang Yu
  • Jun Zhang

Their publications contribute to the domains of cognitive neuroscience and neural engineering, utilizing advanced techniques in EEG data processing, brain-computer interfaces, and neural signal classification. This multifaceted approach combines theoretical and applied research within biomedical and electronic engineering frameworks.

Best Publications

  • Control of a Wheelchair in an Indoor Environment Based on a Brain–Computer Interface and Automated Navigation

    Rui Zhang;Yuanqing Li;Yongyong Yan;Hao Zhang

  • Deep learning based on Batch Normalization for P300 signal detection

    Mingfei Liu;Wei Wu;Zhenghui Gu;Zhuliang Yu

  • Target Selection With Hybrid Feature for BCI-Based 2-D Cursor Control

    Jinyi Long;Yuanqing Li;Tianyou Yu;Zhenghui Gu

  • An asynchronous wheelchair control by hybrid EEG–EOG brain–computer interface

    Hongtao Wang;Hongtao Wang;Yuanqing Li;Jinyi Long;Tianyou Yu

  • Enhanced Motor Imagery Training Using a Hybrid BCI With Feedback

    Tianyou Yu;Jun Xiao;Fangyi Wang;Rui Zhang

  • Robust Adaptive Beamformers Based on Worst-Case Optimization and Constraints on Magnitude Response

    Zhu Liang Yu;Wee Ser;Meng Hwa Er;Zhenghui Gu

  • An EOG-Based Human–Machine Interface for Wheelchair Control

    Qiyun Huang;Shenghong He;Qihong Wang;Zhenghui Gu

  • Motor Imagery Classification Based on Bilinear Sub-Manifold Learning of Symmetric Positive-Definite Matrices

    Xiaofeng Xie;Zhu Liang Yu;Haiping Lu;Zhenghui Gu

  • Voxel Selection in fMRI Data Analysis Based on Sparse Representation

    Yuanqing Li;P. Namburi;Zhuliang Yu;Cuntai Guan

  • Surfing the internet with a BCI mouse

    Tianyou Yu;Yuanqing Li;Jinyi Long;Zhenghui Gu

  • Decoding hand movement velocity from electroencephalogram signals during a drawing task

    Jun Lv;Yuanqing Li;Zhenghui Gu

  • Discrimination Between Control and Idle States in Asynchronous SSVEP-Based Brain Switches: A Pseudo-Key-Based Approach

    Jiahui Pan;Yuanqing Li;Rui Zhang;Zhenghui Gu

  • Sparse Representation for Brain Signal Processing: A tutorial on methods and applications

    Yuanqing Li;Zhu Liang Yu;Ning Bi;Yong Xu

  • Deep Temporal-Spatial Feature Learning for Motor Imagery-Based Brain–Computer Interfaces

    Junjian Chen;Zhuliang Yu;Zhenghui Gu;Yuanqing Li

  • Grouped Automatic Relevance Determination and Its Application in Channel Selection for P300 BCIs

    Tianyou Yu;Zhuliang Yu;Zhenghui Gu;Yuanqing Li

  • Energy-Efficient ECG Compression on Wireless Biosensors via Minimal Coherence Sensing and Weighted $ll_1$ Minimization Reconstruction

    Jun Zhang;Zhenghui Gu;Zhu Liang Yu;Yuanqing Li

  • A Robust Adaptive Beamformer Based on Worst-Case Semi-Definite Programming

    Zhu Liang Yu;Zhenghui Gu;Jianjiang Zhou;Yuanqing Li

  • An Online Semi-supervised Brain–Computer Interface

    Zhenghui Gu;Zhuliang Yu;Zhifang Shen;Yuanqing Li

  • Spatiotemporal-Filtering-Based Channel Selection for Single-Trial EEG Classification

    Feifei Qi;Wei Wu;Zhu Liang Yu;Zhenghui Gu

  • Dilated-Inception Net: Multi-Scale Feature Aggregation for Cardiac Right Ventricle Segmentation

    Jingcong Li;Zhu Liang Yu;Zhenghui Gu;Hui Liu

  • A Novel clustering method based on hybrid K-nearest-neighbor graph

    Yikun Qin;Zhu Liang Yu;Chang-Dong Wang;Zhenghui Gu

Frequent Co-Authors

Zhu Liang Yu
Zhu Liang Yu South China University of Technology
Yuanqing Li
Yuanqing Li South China University of Technology
Jun Zhang
Jun Zhang Nanyang Technological University
Wee Ser
Wee Ser Nanyang Technological University
Srikantan S. Nagarajan
Srikantan S. Nagarajan University of California, San Francisco
Zhiping Lin
Zhiping Lin Nanyang Technological University
Huiling Tan
Huiling Tan University of Oxford
Andrzej Cichocki
Andrzej Cichocki Systems Research Institute
Shun-ichi Amari
Shun-ichi Amari RIKEN Center for Brain Science
Lianwen Jin
Lianwen Jin South China University of Technology

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