Gang Qu

627 total citations
22 papers, 376 citations indexed

About

Gang Qu is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Gang Qu has authored 22 papers receiving a total of 376 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Cognitive Neuroscience, 7 papers in Radiology, Nuclear Medicine and Imaging and 6 papers in Artificial Intelligence. Recurrent topics in Gang Qu's work include Functional Brain Connectivity Studies (16 papers), Advanced Neuroimaging Techniques and Applications (6 papers) and EEG and Brain-Computer Interfaces (4 papers). Gang Qu is often cited by papers focused on Functional Brain Connectivity Studies (16 papers), Advanced Neuroimaging Techniques and Applications (6 papers) and EEG and Brain-Computer Interfaces (4 papers). Gang Qu collaborates with scholars based in United States, China and India. Gang Qu's co-authors include Kwai‐Sang Chin, Shancheng Jiang, Yu‐Ping Wang, Long Wang, Kwok‐Leung Tsui, Vince D. Calhoun, Wenxing Hu, Li Xiao, Kun Zhang and Biao Cai and has published in prestigious journals such as NeuroImage, Expert Systems with Applications and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Gang Qu

19 papers receiving 371 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gang Qu United States 8 134 133 104 53 31 22 376
Imtiaz Ahmed Awan Pakistan 11 82 0.6× 193 1.5× 93 0.9× 98 1.8× 9 0.3× 18 455
Fan Dong United States 10 50 0.4× 64 0.5× 27 0.3× 30 0.6× 12 0.4× 31 288
Mehmed Özkan Türkiye 11 57 0.4× 73 0.5× 76 0.7× 155 2.9× 10 0.3× 52 510
Vladimir Kurbalija Serbia 11 34 0.3× 183 1.4× 16 0.2× 40 0.8× 19 0.6× 35 408
Tabinda Sarwar Australia 8 160 1.2× 46 0.3× 161 1.5× 27 0.5× 5 0.2× 17 326
Aasia Khanum Pakistan 10 22 0.2× 101 0.8× 49 0.5× 48 0.9× 6 0.2× 30 333
Jinduo Liu China 10 158 1.2× 95 0.7× 59 0.6× 10 0.2× 8 0.3× 38 307
Dimitris Liparas Greece 7 78 0.6× 51 0.4× 21 0.2× 22 0.4× 21 0.7× 12 246
Junbo Ma China 9 60 0.4× 187 1.4× 30 0.3× 112 2.1× 5 0.2× 18 328
Qiuling Suo United States 14 83 0.6× 399 3.0× 25 0.2× 83 1.6× 7 0.2× 22 615

Countries citing papers authored by Gang Qu

Since Specialization
Citations

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

Fields of papers citing papers by Gang Qu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gang Qu

This figure shows the co-authorship network connecting the top 25 collaborators of Gang Qu. A scholar is included among the top collaborators of Gang Qu 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 Gang Qu. Gang Qu 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.
Qu, Gang, Ziyu Zhou, Vince D. Calhoun, Aiying Zhang, & Yu‐Ping Wang. (2025). Integrated brain connectivity analysis with fMRI, DTI, and sMRI powered by interpretable graph neural networks. Medical Image Analysis. 103. 103570–103570. 3 indexed citations
2.
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Wang, Yiding, et al.. (2025). A deep spatio-temporal architecture for dynamic ECN analysis with Granger causality based causal discovery. Pattern Recognition. 172(Pt A). 112346–112346. 1 indexed citations
4.
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6.
Patel, Binish, Gang Qu, Tony W. Wilson, et al.. (2024). Explainable Multimodal Graph Isomorphism Network for Interpreting Sex Differences in Adolescent Neurodevelopment. Applied Sciences. 14(10). 4144–4144. 2 indexed citations
7.
Chen, Longyun, Chen Qiao, Gang Qu, et al.. (2024). Explainable spatio-temporal graph evolution learning with applications to dynamic brain network analysis during development. NeuroImage. 298. 120771–120771. 4 indexed citations
8.
Qu, Gang, et al.. (2024). A Deep Dynamic Causal Learning Model to Study Changes in Dynamic Effective Connectivity During Brain Development. IEEE Transactions on Biomedical Engineering. 71(12). 3390–3401. 5 indexed citations
9.
Wang, Wei, Li Xiao, Gang Qu, et al.. (2024). Multiview hyperedge-aware hypergraph embedding learning for multisite, multiatlas fMRI based functional connectivity network analysis. Medical Image Analysis. 94. 103144–103144. 11 indexed citations
10.
Qu, Gang, Gemeng Zhang, Li Xiao, et al.. (2023). Interpretable Cognitive Ability Prediction: A Comprehensive Gated Graph Transformer Framework for Analyzing Functional Brain Networks. IEEE Transactions on Medical Imaging. 43(4). 1568–1578. 6 indexed citations
11.
Li, Hailong, et al.. (2023). Dynamic weighted hypergraph convolutional network for brain functional connectome analysis. Medical Image Analysis. 87. 102828–102828. 30 indexed citations
12.
Qu, Gang, Gemeng Zhang, Binish Patel, et al.. (2022). Latent Similarity Identifies Important Functional Connections for Phenotype Prediction. IEEE Transactions on Biomedical Engineering. 70(6). 1979–1989. 5 indexed citations
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Hu, Wenxing, Xiang‐He Meng, Yuntong Bai, et al.. (2021). Interpretable Multimodal Fusion Networks Reveal Mechanisms of Brain Cognition. IEEE Transactions on Medical Imaging. 40(5). 1474–1483. 40 indexed citations
15.
Qu, Gang, Wenxing Hu, Li Xiao, et al.. (2021). Brain Functional Connectivity Analysis via Graphical Deep Learning. IEEE Transactions on Biomedical Engineering. 69(5). 1696–1706. 20 indexed citations
16.
Qu, Gang, Li Xiao, Wenxing Hu, et al.. (2021). Ensemble Manifold Regularized Multi-Modal Graph Convolutional Network for Cognitive Ability Prediction. IEEE Transactions on Biomedical Engineering. 68(12). 3564–3573. 35 indexed citations
17.
Xiao, Li, Wenxing Hu, Gang Qu, et al.. (2021). Functional network estimation using multigraph learning with application to brain maturation study. Human Brain Mapping. 42(9). 2880–2892. 7 indexed citations
18.
Qu, Gang, Wenxing Hu, Li Xiao, & Yu‐Ping Wang. (2020). A graph deep learning model for the classification of groups with different IQ using resting state fMRI. 9–9. 3 indexed citations
19.
Shi, Xiaoshuang, Hai Su, Fuyong Xing, et al.. (2019). Graph temporal ensembling based semi-supervised convolutional neural network with noisy labels for histopathology image analysis. Medical Image Analysis. 60. 101624–101624. 41 indexed citations
20.
Jiang, Shancheng, Kwai‐Sang Chin, Long Wang, Gang Qu, & Kwok‐Leung Tsui. (2017). Modified genetic algorithm-based feature selection combined with pre-trained deep neural network for demand forecasting in outpatient department. Expert Systems with Applications. 82. 216–230. 113 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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