Boxun Fu

585 total citations · 1 hit paper
11 papers, 427 citations indexed

About

Boxun Fu is a scholar working on Cognitive Neuroscience, Signal Processing and Experimental and Cognitive Psychology. According to data from OpenAlex, Boxun Fu has authored 11 papers receiving a total of 427 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cognitive Neuroscience, 6 papers in Signal Processing and 4 papers in Experimental and Cognitive Psychology. Recurrent topics in Boxun Fu's work include EEG and Brain-Computer Interfaces (10 papers), Blind Source Separation Techniques (6 papers) and Emotion and Mood Recognition (4 papers). Boxun Fu is often cited by papers focused on EEG and Brain-Computer Interfaces (10 papers), Blind Source Separation Techniques (6 papers) and Emotion and Mood Recognition (4 papers). Boxun Fu collaborates with scholars based in China. Boxun Fu's co-authors include Guangming Shi, Fu Li, Yi Niu, Wenming Zheng, Hao Wu, Minghao Dong, Yuchen Li, Yang Li, Li Fu and Yang Li and has published in prestigious journals such as Pattern Recognition, Neurocomputing and Frontiers in Neuroscience.

In The Last Decade

Boxun Fu

11 papers receiving 421 citations

Hit Papers

align trajectories

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.

GMSS: Graph-Based Multi-Task Self-Supervised Learning for EEG Emotion Recognition

2022 122 citations Yang Li, Fu Li et al. IEEE Transactions on Affective Computing profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Boxun Fu China	8	370	188	92	79	66	11	427
Xuyang Zhu China	7	440 1.2×	192 1.0×	53 0.6×	57 0.7×	49 0.7×	11	513
Xuelin Ma China	10	340 0.9×	85 0.5×	79 0.9×	123 1.6×	96 1.5×	13	371
Ruoyu Du China	8	223 0.6×	124 0.7×	50 0.5×	31 0.4×	28 0.4×	28	328
Shaokai Zhao China	7	246 0.7×	104 0.6×	41 0.4×	75 0.9×	32 0.5×	23	313
Wonjun Ko South Korea	9	293 0.8×	75 0.4×	41 0.4×	60 0.8×	76 1.2×	19	343
Virginie Attina France	7	414 1.1×	90 0.5×	78 0.8×	132 1.7×	81 1.2×	19	497
Qiuhao Zeng Singapore	4	280 0.8×	184 1.0×	47 0.5×	19 0.2×	29 0.4×	5	345
Fatemeh Fahimi Singapore	5	344 0.9×	39 0.2×	62 0.7×	92 1.2×	93 1.4×	11	420
Minmin Miao China	13	327 0.9×	42 0.2×	92 1.0×	140 1.8×	78 1.2×	27	412

Countries citing papers authored by Boxun Fu

Since Specialization

Citations

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

Fields of papers citing papers by Boxun Fu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Boxun Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Boxun Fu. A scholar is included among the top collaborators of Boxun Fu 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 Boxun Fu. Boxun Fu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

11 of 11 papers shown

1.

Fu, Boxun, Fu Li, Yang Li, et al.. (2024). Improved Motor Imagery EEG Interdevice Decoding by Reweighting Multisource Domain Samples. IEEE Transactions on Instrumentation and Measurement. 73. 1–12. 2 indexed citations

2.

Li, Fu, et al.. (2024). A novel hybrid decoding neural network for EEG signal representation. Pattern Recognition. 155. 110726–110726. 8 indexed citations

3.

Fu, Boxun, et al.. (2023). SCDAN: Learning Common Feature Representation of Brain Activation for Intersubject Motor Imagery EEG Decoding. IEEE Transactions on Instrumentation and Measurement. 72. 1–15. 12 indexed citations

4.

Li, Yang, Fu Li, Boxun Fu, et al.. (2022). GMSS: Graph-Based Multi-Task Self-Supervised Learning for EEG Emotion Recognition. IEEE Transactions on Affective Computing. 14(3). 2512–2525. 122 indexed citations breakdown →

5.

Li, Fu, et al.. (2022). Decoupling representation learning for imbalanced electroencephalography classification in rapid serial visual presentation task. Journal of Neural Engineering. 19(3). 36011–36011. 8 indexed citations

6.

Li, Fu, Boxun Fu, Yang Li, et al.. (2022). Spatial-temporal network for fine-grained-level emotion EEG recognition. Journal of Neural Engineering. 19(3). 36017–36017. 6 indexed citations

7.

Li, Fu, et al.. (2021). Decoding imagined speech from EEG signals using hybrid-scale spatial-temporal dilated convolution network. Journal of Neural Engineering. 18(4). 0460c4–0460c4. 20 indexed citations

8.

Li, Yang, Boxun Fu, Li Fu, Guangming Shi, & Wenming Zheng. (2021). A novel transferability attention neural network model for EEG emotion recognition. Neurocomputing. 447. 92–101. 90 indexed citations

9.

Fu, Boxun, Fu Li, Yi Niu, et al.. (2020). Conditional generative adversarial network for EEG-based emotion fine-grained estimation and visualization. Journal of Visual Communication and Image Representation. 74. 102982–102982. 17 indexed citations

10.

Wu, Hao, Yi Niu, Fu Li, et al.. (2019). A Parallel Multiscale Filter Bank Convolutional Neural Networks for Motor Imagery EEG Classification. Frontiers in Neuroscience. 13. 1275–1275. 137 indexed citations

11.

Fu, Boxun, et al.. (2019). Single-Shot Colored Speckle Pattern for High Accuracy Depth Sensing. IEEE Sensors Journal. 19(17). 7591–7597. 5 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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