Guangda Liu

1.1k total citations
57 papers, 771 citations indexed

About

Guangda Liu is a scholar working on Biomedical Engineering, Cognitive Neuroscience and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Guangda Liu has authored 57 papers receiving a total of 771 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Biomedical Engineering, 8 papers in Cognitive Neuroscience and 7 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Guangda Liu's work include Non-Invasive Vital Sign Monitoring (9 papers), EEG and Brain-Computer Interfaces (8 papers) and Advanced machining processes and optimization (4 papers). Guangda Liu is often cited by papers focused on Non-Invasive Vital Sign Monitoring (9 papers), EEG and Brain-Computer Interfaces (8 papers) and Advanced machining processes and optimization (4 papers). Guangda Liu collaborates with scholars based in China, United States and Australia. Guangda Liu's co-authors include Munro Peacock, C. Conrad Johnston, Jing Cai, Mark Carey, Walter T. Ambrosius, Siu Hui, Xunbin Wei, Ryan K. Roeder, Charles H. Turner and Tatiana Foroud and has published in prestigious journals such as PLoS ONE, The Journal of Clinical Endocrinology & Metabolism and Journal of Bone and Mineral Research.

In The Last Decade

Guangda Liu

49 papers receiving 744 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Guangda Liu China	15	239	162	137	119	105	57	771
Rosario Salvador‐Palmer Spain	22	138 0.6×	346 2.1×	209 1.5×	72 0.6×	7 0.1×	82	1.6k
Dong Gyu Lee South Korea	20	38 0.2×	103 0.6×	93 0.7×	308 2.6×	41 0.4×	110	1.2k
Zuobing Chen China	18	26 0.1×	190 1.2×	205 1.5×	48 0.4×	58 0.6×	103	1.1k
Kai Yu United States	18	46 0.2×	107 0.7×	459 3.4×	16 0.1×	77 0.7×	50	1.0k
Harbindar Jeet Singh Malaysia	21	57 0.2×	121 0.7×	14 0.1×	50 0.4×	9 0.1×	75	1.2k
Jin-Il Kim South Korea	17	41 0.2×	149 0.9×	124 0.9×	12 0.1×	32 0.3×	90	926
Toshihide Harada Japan	14	24 0.1×	186 1.1×	27 0.2×	13 0.1×	35 0.3×	63	634
László Balogh Hungary	19	54 0.2×	118 0.7×	52 0.4×	15 0.1×	14 0.1×	117	2.2k
Bo He China	22	16 0.1×	238 1.5×	123 0.9×	75 0.6×	48 0.5×	113	1.6k
Wei-Ning Lee Hong Kong	20	117 0.5×	119 0.7×	698 5.1×	47 0.4×	18 0.2×	79	1.6k

Countries citing papers authored by Guangda Liu

Since Specialization

Citations

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

Fields of papers citing papers by Guangda Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guangda Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Guangda Liu. A scholar is included among the top collaborators of Guangda Liu 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 Guangda Liu. Guangda Liu 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:

20 of 20 papers shown

Zhang, Cheng, et al.. (2025). Detecting muscle fatigue during lower limb isometric contractions tasks: a machine learning approach. Frontiers in Physiology. 16. 1547257–1547257.

Wu, Xiaolin, et al.. (2025). Research on the welding strength and V-shape joint structure in the welding of PCD micro tools. International Journal of Refractory Metals and Hard Materials. 132. 107261–107261.

Liu, Guangda, et al.. (2024). The Electroencephalogram (EEG) Study for Estimating Endurance Sports Performance Base on Eigenvalues Extraction Method. Brain Sciences. 14(11). 1135–1135.

Jiang, Feng, Tao Zhang, Qiuling Wen, et al.. (2024). The fabrication of polycrystalline diamond micro drill based on ultrashort pulsed laser. The International Journal of Advanced Manufacturing Technology. 131(12). 5971–5980. 8 indexed citations

Lin, Kai, et al.. (2023). DSE-Mixer: A pure multilayer perceptron network for emotion recognition from EEG feature maps. Journal of Neuroscience Methods. 401. 110008–110008. 7 indexed citations

Wu, Xian, et al.. (2023). Machinability of the uncoated and Ta–C-coated single-flute microdrills in dry machining of PCBs. The International Journal of Advanced Manufacturing Technology. 131(5-6). 2583–2596. 4 indexed citations

Wu, Yiqi, et al.. (2022). A Study on the Relationship between RPE and sEMG in Dynamic Contraction Based on the GPR Method. Electronics. 11(5). 691–691. 4 indexed citations

Cai, Jing, et al.. (2021). Real-Time Arrhythmia Classification Algorithm Using Time-Domain ECG Feature Based on FFNN and CNN. Mathematical Problems in Engineering. 2021. 1–17. 16 indexed citations

Liu, Guangda, et al.. (2021). Minireview of Epilepsy Detection Techniques Based on Electroencephalogram Signals. Frontiers in Systems Neuroscience. 15. 685387–685387. 25 indexed citations

10.

Cai, Jing, et al.. (2021). Application of Electroencephalography-Based Machine Learning in Emotion Recognition: A Review. Frontiers in Systems Neuroscience. 15. 729707–729707. 19 indexed citations

11.

Deng, Wanyu, et al.. (2019). Multiclass heterogeneous domain adaptation via bidirectional ECOC projection. Neural Networks. 119. 313–322. 4 indexed citations

12.

Liu, Guangda, et al.. (2019). SVR-EEMD: An Improved EEMD Method Based on Support Vector Regression Extension in PPG Signal Denoising. Computational and Mathematical Methods in Medicine. 2019. 1–10. 8 indexed citations

13.

Wang, Zhihong, et al.. (2017). Accuracy study for lock‐in amplifiers in a scanning near‐infrared spectrometer. IET Science Measurement & Technology. 11(7). 886–891. 2 indexed citations

14.

Liu, Guangda, Wenzhe Huang, Shiping Ma, & Zhenzhong Wang. (2016). Fingerprint of Dazhu Hongjingtian capsule by HPLC-DAD-QTOF-MS. China Journal of Chinese Materia Medica. 41(16). 3022–3026. 1 indexed citations

15.

Wei, Xunbin, Jianqin Ye, Guangda Liu, et al.. (2012). BF066, a Novel Dual Target Antiplatelet Agent without Significant Bleeding. PLoS ONE. 7(7). e40451–e40451. 16 indexed citations

16.

Li, Yan, Jin Guo, Chaofeng Wang, et al.. (2011). Circulation times of prostate cancer and hepatocellular carcinoma cells by in vivo flow cytometry. Cytometry Part A. 79A(10). 848–854. 36 indexed citations

17.

Li, Suyi, et al.. (2011). A step detection algorithm based-on Chain Code. 24. 164–167. 2 indexed citations

18.

Li, Yan, Zhichao Fan, Jin Guo, et al.. (2010). 应用活体流式细胞仪研究肝癌肿瘤细胞转移. Chinese Optics Letters. 8(10). 953–953. 11 indexed citations

19.

Liu, Guangda, et al.. (2008). Optical synthetic aperture circle-array optimization based on genetic algorithm. Frontiers of Optoelectronics in China. 1(3-4). 268–273.

20.

Wei, Xunbin, Yuan Tan, Yun Chen, et al.. (2008). Monitoring circulating apoptotic cells by in-vivo flow cytometry. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6857. 68570A–68570A. 1 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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