Zhongke Gao

7.5k total citations · 1 hit paper
212 papers, 5.9k citations indexed

About

Zhongke Gao is a scholar working on Cognitive Neuroscience, Economics and Econometrics and Signal Processing. According to data from OpenAlex, Zhongke Gao has authored 212 papers receiving a total of 5.9k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Cognitive Neuroscience, 53 papers in Economics and Econometrics and 45 papers in Signal Processing. Recurrent topics in Zhongke Gao's work include EEG and Brain-Computer Interfaces (59 papers), Complex Systems and Time Series Analysis (53 papers) and Time Series Analysis and Forecasting (35 papers). Zhongke Gao is often cited by papers focused on EEG and Brain-Computer Interfaces (59 papers), Complex Systems and Time Series Analysis (53 papers) and Time Series Analysis and Forecasting (35 papers). Zhongke Gao collaborates with scholars based in China, United Kingdom and Hong Kong. Zhongke Gao's co-authors include Ningde Jin, Yuxuan Yang, Weidong Dang, Qing Cai, Jürgen Kurths, Lusheng Zhai, Xinmin Wang, Chaoxu Mu, Na Dong and Chao Ma and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Zhongke Gao

195 papers receiving 5.8k citations

Hit Papers

EEG-Based Spatio–Temporal Convolutional Neural Network fo... 2019 2026 2021 2023 2019 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. EEG-Based Spatio–Temporal Convolutional Neural Network for Driver Fatigue Evaluation
    2019 369 citations Zhongke Gao, Yuxuan Yang et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Zhongke Gao China 45 1.9k 1.2k 1.1k 1.1k 896 212 5.9k
Lipo Wang Singapore 36 977 0.5× 195 0.2× 505 0.5× 108 0.1× 472 0.5× 185 6.8k
Michael T. Rosenstein United States 21 608 0.3× 616 0.5× 997 0.9× 1.1k 1.1× 78 0.1× 45 4.8k
Chai Quek Singapore 42 1.1k 0.6× 286 0.2× 424 0.4× 67 0.1× 311 0.3× 246 6.3k
Badong Chen China 56 790 0.4× 161 0.1× 735 0.7× 372 0.4× 118 0.1× 462 12.8k
Patrick McSharry United Kingdom 29 811 0.4× 282 0.2× 883 0.8× 122 0.1× 290 0.3× 91 5.9k
Fred Cummins Ireland 21 674 0.4× 147 0.1× 198 0.2× 80 0.1× 779 0.9× 81 5.0k
Felix A. Gers Switzerland 10 324 0.2× 194 0.2× 324 0.3× 142 0.1× 122 0.1× 21 6.3k
George Vachtsevanos United States 43 1.3k 0.7× 114 0.1× 403 0.4× 122 0.1× 60 0.1× 321 8.7k
Abdülhamit Subaşı Saudi Arabia 51 6.0k 3.1× 116 0.1× 2.0k 1.8× 48 0.0× 841 0.9× 178 10.4k
Justin Dauwels Singapore 40 3.3k 1.7× 64 0.1× 299 0.3× 156 0.1× 245 0.3× 267 7.0k

Countries citing papers authored by Zhongke Gao

Since Specialization
Citations

This map shows the geographic impact of Zhongke Gao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Zhongke Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhongke Gao more than expected).

Fields of papers citing papers by Zhongke Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zhongke Gao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Zhongke Gao. The network helps show where Zhongke Gao may publish in the future.

Co-authorship network of co-authors of Zhongke Gao

This figure shows the co-authorship network connecting the top 25 collaborators of Zhongke Gao. A scholar is included among the top collaborators of Zhongke Gao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Zhongke Gao. Zhongke Gao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Cui, Xiaofeng, Yuling He, Mengyu Li, Weidong Cao, & Zhongke Gao. (2025). Complex network-based framework for flow pattern identification in vertical upward oil–water two-phase flow. Physica A Statistical Mechanics and its Applications. 662. 130351–130351. 1 indexed citations
2.
Dong, Na, et al.. (2025). End-to-end autonomous underwater vehicle path following control method based on improved soft actor–critic for deep space exploration. Journal of Industrial Information Integration. 45. 100792–100792. 2 indexed citations
3.
Dang, Weidong, et al.. (2025). An attention-based multiple band interaction network for motor imagery EEG decoding. Applied Soft Computing. 184. 113750–113750.
4.
Wang, Qi, et al.. (2025). AD2T: Multivariate Time-Series Anomaly Detection With Association Discrepancy Dual-Decoder Transformer. IEEE Sensors Journal. 25(7). 11710–11721.
5.
Li, Mengyu, et al.. (2025). APMNet-Based Water-Cut Prediction Using Dual-Helical Microwave Sensing. IEEE Transactions on Instrumentation and Measurement. 74. 1–10. 1 indexed citations
6.
Sun, Xinlin, et al.. (2025). SGL-Net: An Ultralightweight Fatigue Detection Network in Fast Deployment Scenarios. IEEE Transactions on Instrumentation and Measurement. 74. 1–12. 1 indexed citations
7.
Dang, Weidong, et al.. (2024). A novel multiphase flow water cut modeling framework based on flow behavior-heuristic deep learning. Engineering Applications of Artificial Intelligence. 136. 108956–108956. 4 indexed citations
8.
Du, Meng, et al.. (2024). Detecting non-uniform structures in oil-in-water bubbly flow experiments. Physica A Statistical Mechanics and its Applications. 637. 129602–129602. 3 indexed citations
9.
Lv, Dongmei, et al.. (2024). Multilayer Visibility Graph-Based Ordinal Network for Revealing Gas–Liquid Nonlinear Dynamic Flow Behaviors. IEEE Transactions on Instrumentation and Measurement. 73. 1–10. 4 indexed citations
10.
Li, Mengyu, et al.. (2024). Characterization and visualization of gas–liquid two-phase flow based on wire-mesh sensor. Measurement. 243. 116265–116265. 3 indexed citations
11.
Lin, Yi, Zhiyong Qu, Hao Chen, et al.. (2023). Nuclei segmentation with point annotations from pathology images via self-supervised learning and co-training. Medical Image Analysis. 89. 102933–102933. 19 indexed citations
12.
Sun, Xinlin, Chao Ma, Mengyu Li, et al.. (2022). A Novel Complex Network-Based Graph Convolutional Network in Major Depressive Disorder Detection. IEEE Transactions on Instrumentation and Measurement. 71. 1–8. 23 indexed citations
13.
Yang, Yuxuan, et al.. (2021). A CNN identified by reinforcement learning-based optimization framework for EEG-based state evaluation. Journal of Neural Engineering. 18(4). 46059–46059. 21 indexed citations
14.
Gao, Zhongke, et al.. (2021). Attention-Based Parallel Multiscale Convolutional Neural Network for Visual Evoked Potentials EEG Classification. IEEE Journal of Biomedical and Health Informatics. 25(8). 2887–2894. 21 indexed citations
15.
Gao, Zhongke, et al.. (2021). Stage-Wise Densely Connected Network for Parameter Measurement of Two-Phase Flows. IEEE Sensors Journal. 21(16). 18123–18131. 8 indexed citations
16.
Cai, Qing, et al.. (2021). COVID-19 Screening in Chest X-Ray Images Using Lung Region Priors. IEEE Journal of Biomedical and Health Informatics. 25(11). 4119–4127. 14 indexed citations
17.
Gao, Zhongke, et al.. (2020). A Deep Branch-Aggregation Network for Recognition of Gas–Liquid Two-Phase Flow Structure. IEEE Transactions on Instrumentation and Measurement. 70. 1–8. 17 indexed citations
18.
Gao, Zhongke, et al.. (2020). Complex Network Analysis of Experimental EEG Signals for Decoding Brain Cognitive State. IEEE Transactions on Circuits & Systems II Express Briefs. 68(1). 531–535. 9 indexed citations
19.
Gao, Zhongke, et al.. (2020). A Deep Learning Method for Improving the Classification Accuracy of SSMVEP-Based BCI. IEEE Transactions on Circuits & Systems II Express Briefs. 67(12). 3447–3451. 34 indexed citations
20.
Gao, Zhongke, et al.. (2019). Complex Network Analysis of Wire-Mesh Sensor Measurements for Characterizing Vertical Gas–Liquid Two-Phase Flows. IEEE Transactions on Circuits & Systems II Express Briefs. 67(6). 1134–1138. 11 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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