Yonghao Song

1.5k total citations · 1 hit paper
29 papers, 797 citations indexed

About

Yonghao Song is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Artificial Intelligence. According to data from OpenAlex, Yonghao Song has authored 29 papers receiving a total of 797 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Cognitive Neuroscience, 8 papers in Cellular and Molecular Neuroscience and 8 papers in Artificial Intelligence. Recurrent topics in Yonghao Song's work include EEG and Brain-Computer Interfaces (18 papers), Neuroscience and Neural Engineering (8 papers) and Gaze Tracking and Assistive Technology (6 papers). Yonghao Song is often cited by papers focused on EEG and Brain-Computer Interfaces (18 papers), Neuroscience and Neural Engineering (8 papers) and Gaze Tracking and Assistive Technology (6 papers). Yonghao Song collaborates with scholars based in China, Hong Kong and Singapore. Yonghao Song's co-authors include Xiaorong Gao, Qingqing Zheng, Bingchuan Liu, Longhan Xie, Lie Yang, Ke Ma, Hongshen Chen, Xiaofang Zhao, Hengyi Cai and Dawei Yin and has published in prestigious journals such as NeuroImage, Expert Systems with Applications and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Yonghao Song

26 papers receiving 780 citations

Hit Papers

EEG Conformer: Convolutional Transformer for EEG Decoding... 2022 2026 2023 2024 2022 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 Conformer: Convolutional Transformer for EEG Decoding and Visualization
    2022 361 citations Yonghao Song, Qingqing Zheng et al. IEEE Transactions on Neural Systems and Rehabilitation Engineering profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yonghao Song China 14 566 186 155 145 130 29 797
Brent J. Lance United States 19 749 1.3× 128 0.7× 170 1.1× 224 1.5× 150 1.2× 38 1.0k
Dong-Ok Won South Korea 12 487 0.9× 140 0.8× 190 1.2× 114 0.8× 97 0.7× 46 751
Mingai Li China 18 533 0.9× 141 0.8× 233 1.5× 107 0.7× 148 1.1× 94 807
Vernon J. Lawhern United States 17 811 1.4× 134 0.7× 231 1.5× 130 0.9× 205 1.6× 40 999
Zhao Lv China 17 526 0.9× 152 0.8× 105 0.7× 255 1.8× 59 0.5× 85 888
Yunyuan Gao China 17 636 1.1× 123 0.7× 95 0.6× 101 0.7× 62 0.5× 59 898
Yuliang Ma China 18 527 0.9× 150 0.8× 93 0.6× 85 0.6× 87 0.7× 51 840
D. N. Tibarewala India 16 505 0.9× 70 0.4× 176 1.1× 203 1.4× 92 0.7× 65 745
Sachin Taran India 14 582 1.0× 95 0.5× 183 1.2× 120 0.8× 140 1.1× 38 846
Mehmet İsmail Gürsoy Türkiye 7 721 1.3× 189 1.0× 129 0.8× 79 0.5× 79 0.6× 14 963

Countries citing papers authored by Yonghao Song

Since Specialization
Citations

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

Fields of papers citing papers by Yonghao Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yonghao Song

This figure shows the co-authorship network connecting the top 25 collaborators of Yonghao Song. A scholar is included among the top collaborators of Yonghao Song 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 Yonghao Song. Yonghao Song 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.
Wu, Jiamin, et al.. (2025). Neuro-3D: Towards 3D Visual Decoding from EEG Signals. 23870–23880.
2.
Song, Yonghao, Yijun Wang, Huiguang He, & Xiaorong Gao. (2025). Recognizing Natural Images From EEG With Language-Guided Contrastive Learning. IEEE Transactions on Neural Networks and Learning Systems. 36(9). 15896–15910. 1 indexed citations
3.
Song, Yonghao, et al.. (2024). Unsupervised multi-source domain adaptation via contrastive learning for EEG classification. Expert Systems with Applications. 261. 125452–125452. 9 indexed citations
4.
Shi, Nanlin, et al.. (2024). High-performance c-VEP-BCI under minimal calibration. Expert Systems with Applications. 249. 123679–123679. 7 indexed citations
5.
Shi, Nanlin, et al.. (2024). Estimating and approaching the maximum information rate of noninvasive visual brain-computer interface. NeuroImage. 289. 120548–120548. 11 indexed citations
6.
Chen, Lilin, et al.. (2024). Prediction of 6-Mo Poststroke Spasticity in Patients With Acute First-Ever Stroke by Machine Learning. American Journal of Physical Medicine & Rehabilitation. 103(12). 1123–1129.
7.
Song, Yonghao, Qingqing Zheng, Qiong Wang, Xiaorong Gao, & Pheng‐Ann Heng. (2023). Global Adaptive Transformer for Cross-Subject Enhanced EEG Classification. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31. 2767–2777. 29 indexed citations
8.
Song, Yonghao, Qingqing Zheng, Bingchuan Liu, & Xiaorong Gao. (2022). EEG Conformer: Convolutional Transformer for EEG Decoding and Visualization. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31. 710–719. 361 indexed citations breakdown →
9.
Song, Yonghao, et al.. (2022). Excellent fine-tuning: From specific-subject classification to cross-task classification for motor imagery. Biomedical Signal Processing and Control. 79. 104051–104051. 19 indexed citations
10.
Yang, Lie, et al.. (2021). Two-branch 3D convolutional neural network for motor imagery EEG decoding. Journal of Neural Engineering. 18(4). 0460c7–0460c7. 11 indexed citations
11.
Xu, Yuan, et al.. (2021). Improving Sequential Recommendation Consistency with Self-Supervised Imitation. 3321–3327. 12 indexed citations
12.
Yang, Lie, Yonghao Song, Ke Ma, & Longhan Xie. (2021). Motor Imagery EEG Decoding Method Based on a Discriminative Feature Learning Strategy. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 29. 368–379. 79 indexed citations
13.
14.
Cai, Siqi, et al.. (2020). Low Latency Auditory Attention Detection with Common Spatial Pattern Analysis of EEG Signals. 2772–2776. 19 indexed citations
15.
Song, Yonghao, Siqi Cai, Lie Yang, et al.. (2020). A Practical EEG-Based Human-Machine Interface to Online Control an Upper-Limb Assist Robot. Frontiers in Neurorobotics. 14. 32–32. 18 indexed citations
16.
Cai, Hengyi, Hongshen Chen, Cheng Zhang, et al.. (2020). Learning from Easy to Complex: Adaptive Multi-Curricula Learning for Neural Dialogue Generation. Proceedings of the AAAI Conference on Artificial Intelligence. 34(5). 7472–7479. 17 indexed citations
17.
Cai, Hengyi, Hongshen Chen, Yonghao Song, Xiaofang Zhao, & Dawei Yin. (2020). Exemplar Guided Neural Dialogue Generation. 3601–3607. 6 indexed citations
18.
Song, Yonghao, et al.. (2020). Assistive Mobile Robot with Shared Control of Brain-Machine Interface and Computer Vision. 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC). 405–409. 2 indexed citations
19.
Cai, Hengyi, Hongshen Chen, Yonghao Song, et al.. (2020). Group-wise Contrastive Learning for Neural Dialogue Generation. 793–802. 21 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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