Guangzhen Liu

503 total citations · 1 hit paper
15 papers, 202 citations indexed

About

Guangzhen Liu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Guangzhen Liu has authored 15 papers receiving a total of 202 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 5 papers in Electrical and Electronic Engineering. Recurrent topics in Guangzhen Liu's work include Multimodal Machine Learning Applications (3 papers), Autonomous Vehicle Technology and Safety (2 papers) and Advanced Battery Technologies Research (2 papers). Guangzhen Liu is often cited by papers focused on Multimodal Machine Learning Applications (3 papers), Autonomous Vehicle Technology and Safety (2 papers) and Advanced Battery Technologies Research (2 papers). Guangzhen Liu collaborates with scholars based in China, Sweden and United Kingdom. Guangzhen Liu's co-authors include Rui Li, Yunzhi Xue, Zhiwu Lu, Guoxing Yang, Nanyi Fei, Tao Xiang, Mingyu Ding, Xueyuan Chen, Lu‐Fang Ma and Jiaojiao Wei and has published in prestigious journals such as Coordination Chemistry Reviews, IEEE Access and Molecular Immunology.

In The Last Decade

Guangzhen Liu

12 papers receiving 192 citations

Hit Papers

A survey on dataset quality in machine learning 2023 2026 2024 2025 2023 40 80 120
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.

  1. A survey on dataset quality in machine learning
    2023 120 citations Guangzhen Liu, Yunzhi Xue et al. Information and Software Technology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Guangzhen Liu China 6 58 50 27 21 18 15 202
Nitin Kumar Chauhan India 5 37 0.6× 109 2.2× 23 0.9× 11 0.5× 17 0.9× 9 273
J. Surendiran India 10 36 0.6× 47 0.9× 43 1.6× 16 0.8× 5 0.3× 28 209
Zhihui Xiong China 9 82 1.4× 20 0.4× 56 2.1× 19 0.9× 15 0.8× 52 274
S. Agnes Shifani India 8 27 0.5× 27 0.5× 33 1.2× 9 0.4× 6 0.3× 27 144
Saidul Islam Canada 3 32 0.6× 71 1.4× 50 1.9× 10 0.5× 5 0.3× 5 215
ElSayed M. Tag El Din Egypt 7 20 0.3× 37 0.7× 67 2.5× 28 1.3× 16 0.9× 10 272
Ziqiang Li China 11 49 0.8× 86 1.7× 62 2.3× 6 0.3× 12 0.7× 25 349
D. Saravanan India 8 71 1.2× 34 0.7× 34 1.3× 9 0.4× 6 0.3× 35 171
Muhammad Rehman Zafar Pakistan 3 22 0.4× 114 2.3× 18 0.7× 7 0.3× 8 0.4× 4 227

Countries citing papers authored by Guangzhen Liu

Since Specialization
Citations

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

Fields of papers citing papers by Guangzhen Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guangzhen Liu

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

All Works

15 of 15 papers shown
1.
Wang, Mengjiao, Min Guo, Yuetao Liu, et al.. (2025). The protective role of Astragaloside IV in adriamycin-induced renal injury: A focus on macrophage polarization and PPARγ activation. Molecular Immunology. 186. 161–173.
2.
Wei, Jiaojiao, Guangzhen Liu, Hong‐Ru Fu, et al.. (2024). Doping engineering of lead halide perovskite nanocrystals for advanced optoelectronic applications. Coordination Chemistry Reviews. 519. 216119–216119. 10 indexed citations
3.
Li, Qian, Guangzhen Liu, Xiaoguang Ma, et al.. (2023). Study on the Effectiveness of Water Mist on Suppressing Thermal Runaway in LiFePO4 Batteries. Crystals. 13(9). 1346–1346. 6 indexed citations
4.
Liu, Guangzhen, et al.. (2023). A survey on dataset quality in machine learning. Information and Software Technology. 162. 107268–107268. 120 indexed citations breakdown →
5.
Guo, Heng, et al.. (2023). ECSAS: Exploring Critical Scenarios from Action Sequence in Autonomous Driving. 1–6. 4 indexed citations
6.
Chen, He, et al.. (2022). A Survey of Autonomous Driving Scenarios and Scenario Databases. 754–762. 6 indexed citations
7.
Liu, Guangzhen & Zhiwu Lu. (2021). Weakly-Supervised Attribute Segmentation. 1–6.
8.
Yang, Guoxing, Nanyi Fei, Mingyu Ding, et al.. (2021). L2M-GAN: Learning to Manipulate Latent Space Semantics for Facial Attribute Editing. 2950–2959. 35 indexed citations
9.
10.
Liu, Guangzhen, et al.. (2020). Intelligent substation fault diagnosis based on optimization support vector machine. IOP Conference Series Earth and Environmental Science. 526(1). 12101–12101. 1 indexed citations
11.
Liu, Liqing, et al.. (2020). Analysis of Activation Energy of Epoxy Resin Insulated Transformer Based on Dynamic Method. IOP Conference Series Materials Science and Engineering. 782(2). 22116–22116.
12.
Liu, Guangzhen & Zhiwu Lu. (2020). Discriminativeness-Preserved Domain Adaptation for Few-Shot Learning. IEEE Access. 8. 168405–168413. 3 indexed citations
13.
Liu, Guangzhen, et al.. (2019). Joint Projection and Subspace Learning for Zero-Shot Recognition. 1228–1233. 5 indexed citations
14.
Zhang, Xin, et al.. (2018). Transformers Condition Evaluation Based on Bayesian Classifier. IOP Conference Series Materials Science and Engineering. 452. 42031–42031. 4 indexed citations
15.
Liu, Guangzhen, et al.. (2017). Graph-boosted convolutional neural networks for semantic segmentation. 612–618. 4 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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