Anmin Gong

596 total citations
46 papers, 365 citations indexed

About

Anmin Gong is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Human-Computer Interaction. According to data from OpenAlex, Anmin Gong has authored 46 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Cognitive Neuroscience, 13 papers in Cellular and Molecular Neuroscience and 9 papers in Human-Computer Interaction. Recurrent topics in Anmin Gong's work include EEG and Brain-Computer Interfaces (40 papers), Neuroscience and Neural Engineering (13 papers) and Neural dynamics and brain function (10 papers). Anmin Gong is often cited by papers focused on EEG and Brain-Computer Interfaces (40 papers), Neuroscience and Neural Engineering (13 papers) and Neural dynamics and brain function (10 papers). Anmin Gong collaborates with scholars based in China, Switzerland and Iran. Anmin Gong's co-authors include Yunfa Fu, Changhao Jiang, Fan Wang, Lei Su, Jianping Liu, Yi Qu, Fengshou Gu, Wenya Nan, Qian Qian and Si Chen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Neuroscience and Neuropsychologia.

In The Last Decade

Anmin Gong

42 papers receiving 358 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Anmin Gong China	12	300	76	55	48	45	46	365
Dariusz Zapała Poland	11	280 0.9×	86 1.1×	27 0.5×	46 1.0×	42 0.9×	26	366
Wenya Nan China	13	576 1.9×	121 1.6×	83 1.5×	29 0.6×	38 0.8×	38	663
Davide Borra Italy	12	271 0.9×	79 1.0×	54 1.0×	66 1.4×	24 0.5×	23	377
Simon Ladouce France	9	299 1.0×	48 0.6×	28 0.5×	27 0.6×	37 0.8×	20	387
Takeshi Sakurada Japan	9	255 0.8×	95 1.3×	25 0.5×	111 2.3×	44 1.0×	37	391
Niki Pandria Greece	12	211 0.7×	64 0.8×	45 0.8×	35 0.7×	46 1.0×	28	374
Alkinoos Athanasiou Greece	11	253 0.8×	89 1.2×	39 0.7×	79 1.6×	55 1.2×	35	413
Szczepan Paszkiel Poland	10	139 0.5×	37 0.5×	30 0.5×	50 1.0×	34 0.8×	37	257
Sarah Blum Germany	8	311 1.0×	52 0.7×	30 0.5×	39 0.8×	28 0.6×	12	375
Luz María Alonso-Valerdi Mexico	11	217 0.7×	52 0.7×	30 0.5×	40 0.8×	37 0.8×	53	348

Countries citing papers authored by Anmin Gong

Since Specialization

Citations

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

Fields of papers citing papers by Anmin Gong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anmin Gong

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

All Works

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20 of 20 papers shown

Chen, Yijun, et al.. (2025). UAV Identification via Multiscale Decision Fusion CNN Utilizing Micro-Doppler Features. IEEE Geoscience and Remote Sensing Letters. 22. 1–5.

Ding, Peng, et al.. (2024). Emotion Classification Based on Transformer and CNN for EEG Spatial–Temporal Feature Learning. Brain Sciences. 14(3). 268–268. 17 indexed citations

Shi, Kelvin, et al.. (2024). Intermediary-guided windowed attention Aggregation network for fine-grained characterization of Major Depressive Disorder fMRI. Biomedical Signal Processing and Control. 100. 107166–107166.

Wang, Fan, et al.. (2024). Brain-computer interface paradigms and neural coding. Frontiers in Neuroscience. 17. 1345961–1345961. 16 indexed citations

Shi, Qi, Anmin Gong, Peng Ding, Fan Wang, & Yunfa Fu. (2023). Neural Mechanisms of Visual–Spatial Judgment Behavior under Visual and Auditory Constraints: Evidence from an Electroencephalograph during Handgun Shooting. Brain Sciences. 13(12). 1702–1702. 1 indexed citations

Gong, Anmin, et al.. (2023). Cross-Domain Identification of Multisite Major Depressive Disorder Using End-to-End Brain Dynamic Attention Network. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 32. 33–42. 3 indexed citations

Zeng, Jia, et al.. (2023). High vagally mediated resting-state heart rate variability is associated with superior working memory function. Frontiers in Neuroscience. 17. 1119405–1119405. 9 indexed citations

Saemi, Esmaeel, et al.. (2023). Neurofeedback training and motor learning: the enhanced sensorimotor rhythm protocol is better or the suppressed alpha or the suppressed mu?. BMC Sports Science Medicine and Rehabilitation. 15(1). 93–93. 7 indexed citations

Wang, Fan, et al.. (2022). Improved Brain–Computer Interface Signal Recognition Algorithm Based on Few-Channel Motor Imagery. Frontiers in Human Neuroscience. 16. 880304–880304. 8 indexed citations

10.

Ding, Peng, et al.. (2022). [Applications, industrial transformation and commercial value of brain-computer interface technology].. PubMed. 39(2). 405–415. 4 indexed citations

11.

Gong, Anmin, et al.. (2022). [Key technologies for intelligent brain-computer interaction based on magnetoencephalography].. PubMed. 39(1). 198–206. 4 indexed citations

12.

Gu, Fengshou, et al.. (2022). Brain Network Research of Skilled Shooters in the Shooting Preparation Stage under the Condition of Limited Sensory Function. Brain Sciences. 12(10). 1373–1373. 1 indexed citations

13.

Gong, Anmin, et al.. (2021). Decoding of Walking Imagery and Idle State Using Sparse Representation Based on fNIRS. Computational Intelligence and Neuroscience. 2021(1). 6614112–6614112. 6 indexed citations

14.

Ding, Peng, Siyu Li, Yaoguang Zhang, et al.. (2021). Monitoring and Evaluation of Emotion Regulation by Aerobic Exercise and Motor Imagery Based on Functional Near-Infrared Spectroscopy. Frontiers in Computational Neuroscience. 15. 2 indexed citations

15.

Li, Siyu, et al.. (2021). Identification of Emotion Using Electroencephalogram by Tunable Q-Factor Wavelet Transform and Binary Gray Wolf Optimization. Frontiers in Computational Neuroscience. 15. 732763–732763. 6 indexed citations

16.

Fu, Yunfa, et al.. (2021). Recognition of Flexion and Extension Imagery Involving the Right and Left Arms Based on Deep Belief Network and Functional Near-Infrared Spectroscopy. Journal of Healthcare Engineering. 2021. 1–11. 6 indexed citations

17.

Fu, Yunfa, et al.. (2021). Decoding of Motor Coordination Imagery Involving the Lower Limbs by the EEG‐Based Brain Network. Computational Intelligence and Neuroscience. 2021(1). 5565824–5565824. 9 indexed citations

18.

Shao, Mingming, et al.. (2020). Effect of shooting experience on executive function: differences between experts and novices. PeerJ. 8. e9802–e9802. 7 indexed citations

19.

Gong, Anmin, Jianping Liu, Changhao Jiang, & Yunfa Fu. (2018). Rifle Shooting Performance Correlates with Electroencephalogram Beta Rhythm Network Activity during Aiming. Computational Intelligence and Neuroscience. 2018. 1–11. 13 indexed citations

20.

Gong, Anmin, et al.. (2017). Correlation Between Resting-state Electroencephalographic Characteristics and Shooting Performance. Neuroscience. 366. 172–183. 10 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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