Chao Ma

3.4k total citations · 1 hit paper
106 papers, 2.6k citations indexed

About

Chao Ma is a scholar working on Cognitive Neuroscience, Global and Planetary Change and Water Science and Technology. According to data from OpenAlex, Chao Ma has authored 106 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Cognitive Neuroscience, 19 papers in Global and Planetary Change and 18 papers in Water Science and Technology. Recurrent topics in Chao Ma's work include EEG and Brain-Computer Interfaces (18 papers), Flood Risk Assessment and Management (14 papers) and Functional Brain Connectivity Studies (14 papers). Chao Ma is often cited by papers focused on EEG and Brain-Computer Interfaces (18 papers), Flood Risk Assessment and Management (14 papers) and Functional Brain Connectivity Studies (14 papers). Chao Ma collaborates with scholars based in China, United States and Canada. Chao Ma's co-authors include Jijian Lian, Kui Xu, Hongshi Xu, Zhongke Gao, Lingling Bin, Evance Chaima, Weichao Yang, Zhanjun Zhang, Xinlin Sun and Guicai Zhang and has published in prestigious journals such as Chemical Engineering Journal, Journal of Hydrology and Nano Energy.

In The Last Decade

Chao Ma

100 papers receiving 2.5k citations

Hit Papers

Urban flooding risk assessment based on an integrated k-m... 2018 2026 2020 2023 2018 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. Urban flooding risk assessment based on an integrated k-means cluster algorithm and improved entropy weight method in the region of Haikou, China
    2018 337 citations Chao Ma, Jijian Lian et al. Journal of Hydrology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chao Ma China 27 678 453 412 323 239 106 2.6k
Amit Bhattacharya India 30 315 0.5× 214 0.5× 138 0.3× 146 0.5× 274 1.1× 223 3.7k
Ge Chen China 31 842 1.2× 145 0.3× 134 0.3× 180 0.6× 261 1.1× 287 3.9k
Yuan Zhou China 24 132 0.2× 299 0.7× 330 0.8× 121 0.4× 209 0.9× 102 2.4k
Jintao Wu China 21 306 0.5× 126 0.3× 170 0.4× 80 0.2× 127 0.5× 144 2.1k
Chi Zhang China 23 238 0.4× 433 1.0× 193 0.5× 48 0.1× 172 0.7× 107 1.7k
Ke Li China 26 245 0.4× 853 1.9× 253 0.6× 194 0.6× 271 1.1× 201 2.8k
Xiang Zhang China 43 2.3k 3.3× 159 0.4× 1.0k 2.5× 427 1.3× 199 0.8× 241 5.8k
David G. Groves United States 22 873 1.3× 167 0.4× 563 1.4× 703 2.2× 93 0.4× 78 2.9k
Changhai Li China 34 237 0.3× 91 0.2× 182 0.4× 623 1.9× 312 1.3× 203 3.8k
Jiayi Li China 34 904 1.3× 68 0.2× 138 0.3× 251 0.8× 168 0.7× 164 3.9k

Countries citing papers authored by Chao Ma

Since Specialization
Citations

This map shows the geographic impact of Chao Ma'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 Chao Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chao Ma more than expected).

Fields of papers citing papers by Chao Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chao Ma. 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 Chao Ma. The network helps show where Chao Ma may publish in the future.

Co-authorship network of co-authors of Chao Ma

This figure shows the co-authorship network connecting the top 25 collaborators of Chao Ma. A scholar is included among the top collaborators of Chao Ma 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 Chao Ma. Chao Ma 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.
Dong, Ruili, et al.. (2025). Effects of Hydrogen Peroxide Soaking on the Seeds of Different Edible Bean Varieties. Plants. 14(22). 3476–3476.
2.
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
3.
Liu, Xiaofeng, Chao Ma, Xiong Yang, et al.. (2025). Unsupervised Domain Adaptation With Synchronized Self-Training for Cross- Domain Motor Imagery Recognition. IEEE Journal of Biomedical and Health Informatics. 29(5). 3664–3677. 1 indexed citations
4.
5.
Ma, Chao, et al.. (2024). Hybrid LSTM–Transformer Model for the Prediction of Epileptic Seizure Using Scalp EEG. IEEE Sensors Journal. 24(13). 21123–21131. 12 indexed citations
6.
Ma, Chao, et al.. (2023). Co-Attention-Based Cross-Stitch Network for Parameter Prediction of Two-Phase Flow. IEEE Transactions on Instrumentation and Measurement. 72. 1–12. 9 indexed citations
7.
Ma, Chao, et al.. (2023). Dynamic Threshold Distribution Domain Adaptation Network: A Cross-Subject Fatigue Recognition Method Based on EEG Signals. IEEE Transactions on Cognitive and Developmental Systems. 16(1). 190–201. 8 indexed citations
8.
Niu, W. D., Chao Ma, Xinlin Sun, Mengyu Li, & Zhongke Gao. (2023). A Brain Network Analysis-Based Double Way Deep Neural Network for Emotion Recognition. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31. 917–925. 28 indexed citations
9.
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
10.
Sun, Biao, et al.. (2022). A Multiscale Feature Extraction Network Based on Channel-Spatial Attention for Electromyographic Signal Classification. IEEE Transactions on Cognitive and Developmental Systems. 15(2). 591–601. 26 indexed citations
11.
Li, Mengyu, et al.. (2022). DSCNN: Dilated Shuffle CNN Model for SSVEP Signal Classification. IEEE Sensors Journal. 22(12). 12036–12043. 16 indexed citations
12.
Zhu, Xinshan, et al.. (2021). A gradient-based automatic optimization CNN framework for EEG state recognition. Journal of Neural Engineering. 19(1). 16009–16009. 11 indexed citations
13.
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
14.
Gao, Zhongke, et al.. (2021). Core-Brain-Network-Based Multilayer Convolutional Neural Network for Emotion Recognition. IEEE Transactions on Instrumentation and Measurement. 70. 1–9. 51 indexed citations
15.
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
16.
Gao, Zhongke, et al.. (2020). Characterization of Two-Phase Flow Structure by Deep Learning-Based Super Resolution. IEEE Transactions on Circuits & Systems II Express Briefs. 68(2). 782–786. 7 indexed citations
17.
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
18.
Sun, Xinlin, et al.. (2020). A Multifrequency Brain Network-Based Deep Learning Framework for Motor Imagery Decoding. Neural Plasticity. 2020. 1–11. 16 indexed citations
19.
Yang, Weichao, Kui Xu, Jijian Lian, Chao Ma, & Lingling Bin. (2018). Integrated flood vulnerability assessment approach based on TOPSIS and Shannon entropy methods. Ecological Indicators. 89. 269–280. 171 indexed citations
20.

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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