Shuyue Jia

597 total citations
9 papers, 385 citations indexed

About

Shuyue Jia is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience and Biomedical Engineering. According to data from OpenAlex, Shuyue Jia has authored 9 papers receiving a total of 385 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Electrical and Electronic Engineering, 3 papers in Cognitive Neuroscience and 3 papers in Biomedical Engineering. Recurrent topics in Shuyue Jia's work include EEG and Brain-Computer Interfaces (3 papers), Advanced Image Fusion Techniques (2 papers) and Image and Video Quality Assessment (2 papers). Shuyue Jia is often cited by papers focused on EEG and Brain-Computer Interfaces (3 papers), Advanced Image Fusion Techniques (2 papers) and Image and Video Quality Assessment (2 papers). Shuyue Jia collaborates with scholars based in China, Hong Kong and Australia. Shuyue Jia's co-authors include Yimin Hou, Xiangmin Lun, Yan Shi, Yang Li, Jinglei Lv, Rui Zeng, Jingjing Liu, Hong Men, Yuanzheng Li and Qi Zhang and has published in prestigious journals such as Journal of Membrane Science, Sensors and Actuators B Chemical and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Shuyue Jia

9 papers receiving 376 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shuyue Jia China	8	205	121	91	78	49	9	385
Peng Yuan China	8	143 0.7×	63 0.5×	41 0.5×	73 0.9×	28 0.6×	15	330
Akshay Kumar India	12	125 0.6×	84 0.7×	41 0.5×	31 0.4×	33 0.7×	44	405
Nasir Rashid Pakistan	13	94 0.5×	38 0.3×	148 1.6×	48 0.6×	27 0.6×	40	428
C.R. Hema Malaysia	10	199 1.0×	34 0.3×	37 0.4×	69 0.9×	86 1.8×	38	359
Xiaochen Tang United States	12	107 0.5×	109 0.9×	211 2.3×	25 0.3×	24 0.5×	36	497
Mariusz Pelc United Kingdom	11	290 1.4×	52 0.4×	86 0.9×	90 1.2×	25 0.5×	72	520
Önder Aydemir Türkiye	15	372 1.8×	89 0.7×	187 2.1×	158 2.0×	67 1.4×	63	590
Hung-Yi Hsieh Taiwan	9	130 0.6×	215 1.8×	256 2.8×	75 1.0×	42 0.9×	23	477
Mohammed Algabri Saudi Arabia	11	143 0.7×	71 0.6×	80 0.9×	71 0.9×	130 2.7×	29	537

Countries citing papers authored by Shuyue Jia

Since Specialization

Citations

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

Fields of papers citing papers by Shuyue Jia

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuyue Jia

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

All Works

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9 of 9 papers shown

Jia, Shuyue, Jovan Tan, Zhengzhong Zhou, & Sui Zhang. (2025). A sustainable method to prepare ultra-thin MOF hollow fiber membranes for H2 separation. Journal of Membrane Science. 721. 123794–123794. 3 indexed citations

Jia, Shuyue, et al.. (2023). Learning from mixed datasets: A monotonic image quality assessment model. Electronics Letters. 59(3). 8 indexed citations

Li, Yang, et al.. (2023). PMU Measurements-Based Short-Term Voltage Stability Assessment of Power Systems via Deep Transfer Learning. IEEE Transactions on Instrumentation and Measurement. 72. 1–11. 39 indexed citations

Hou, Yimin, Shuyue Jia, Xiangmin Lun, et al.. (2022). Deep Feature Mining via the Attention-Based Bidirectional Long Short Term Memory Graph Convolutional Neural Network for Human Motor Imagery Recognition. Frontiers in Bioengineering and Biotechnology. 9. 706229–706229. 26 indexed citations

Hou, Yimin, Shuyue Jia, Xiangmin Lun, et al.. (2022). GCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-Resolved EEG Motor Imagery Signals. IEEE Transactions on Neural Networks and Learning Systems. 35(6). 7312–7323. 101 indexed citations

Jia, Shuyue, Baoliang Chen, Dingquan Li, & Shiqi Wang. (2022). No-reference Image Quality Assessment via Non-local Dependency Modeling. 1–6. 7 indexed citations

Shi, Yan, et al.. (2021). Improving performance: A collaborative strategy for the multi-data fusion of electronic nose and hyperspectral to track the quality difference of rice. Sensors and Actuators B Chemical. 333. 129546–129546. 59 indexed citations

Shi, Yan, et al.. (2020). Origin traceability of rice based on an electronic nose coupled with a feature reduction strategy. Measurement Science and Technology. 32(2). 25107–25107. 24 indexed citations

Hou, Yimin, et al.. (2019). A novel approach of decoding EEG four-class motor imagery tasks via scout ESI and CNN. Journal of Neural Engineering. 17(1). 16048–16048. 118 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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