Gongfa Chen

1.4k total citations
44 papers, 1.0k citations indexed

About

Gongfa Chen is a scholar working on Civil and Structural Engineering, Environmental Engineering and Building and Construction. According to data from OpenAlex, Gongfa Chen has authored 44 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Civil and Structural Engineering, 8 papers in Environmental Engineering and 7 papers in Building and Construction. Recurrent topics in Gongfa Chen's work include Infrastructure Maintenance and Monitoring (19 papers), Structural Health Monitoring Techniques (12 papers) and Concrete Corrosion and Durability (8 papers). Gongfa Chen is often cited by papers focused on Infrastructure Maintenance and Monitoring (19 papers), Structural Health Monitoring Techniques (12 papers) and Concrete Corrosion and Durability (8 papers). Gongfa Chen collaborates with scholars based in China, Singapore and Hong Kong. Gongfa Chen's co-authors include Shuai Teng, Haibo Jiang, Zhuangcheng Fang, Zuxiang Situ, Qianqian Zhou, Fangsen Cui, Cheng Li, Xingjun Gao, Xuedi Chen and Jiqiao Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computer Methods in Applied Mechanics and Engineering and Journal of Biomechanics.

In The Last Decade

Gongfa Chen

43 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gongfa Chen China 19 783 281 141 119 91 44 1.0k
Mayank Mishra India 21 837 1.1× 135 0.5× 151 1.1× 152 1.3× 44 0.5× 44 1.3k
Shuai Teng China 21 781 1.0× 95 0.3× 132 0.9× 202 1.7× 110 1.2× 72 1.1k
Qiubing Ren China 21 927 1.2× 119 0.4× 128 0.9× 151 1.3× 54 0.6× 57 1.3k
Seung Woo Lee South Korea 16 514 0.7× 134 0.5× 84 0.6× 99 0.8× 136 1.5× 110 953
Peixin Shi China 22 965 1.2× 173 0.6× 89 0.6× 124 1.0× 86 0.9× 75 1.4k
Ehsan Noroozinejad Farsangi Iran 24 1.9k 2.5× 507 1.8× 109 0.8× 200 1.7× 28 0.3× 196 2.3k
Tom Iseley United States 20 1.0k 1.3× 141 0.5× 131 0.9× 362 3.0× 90 1.0× 45 1.5k
Junwon Seo United States 18 967 1.2× 236 0.8× 92 0.7× 154 1.3× 86 0.9× 84 1.3k
Mehdi Nikoo Iran 21 1.1k 1.4× 391 1.4× 142 1.0× 145 1.2× 13 0.1× 39 1.4k
Vuong Minh Le Vietnam 13 649 0.8× 207 0.7× 61 0.4× 122 1.0× 15 0.2× 14 1.1k

Countries citing papers authored by Gongfa Chen

Since Specialization
Citations

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

Fields of papers citing papers by Gongfa Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gongfa Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Gongfa Chen. A scholar is included among the top collaborators of Gongfa Chen 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 Gongfa Chen. Gongfa Chen 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.
2.
Situ, Zuxiang, et al.. (2023). A transfer learning-based YOLO network for sewer defect detection in comparison to classic object detection methods. Developments in the Built Environment. 15. 100191–100191. 22 indexed citations
3.
Chen, Gongfa, et al.. (2023). Slope stability analysis based on convolutional neural network and digital twin. Natural Hazards. 118(2). 1427–1443. 14 indexed citations
4.
Zhou, Qianqian, et al.. (2023). A deep-learning-technique-based data-driven model for accurate and rapid flood predictions in temporal and spatial dimensions. Hydrology and earth system sciences. 27(9). 1791–1808. 37 indexed citations
5.
Teng, Shuai, et al.. (2023). Application of convolutional neural networks based on Bayesian optimization to landslide susceptibility mapping of transmission tower foundation. Bulletin of Engineering Geology and the Environment. 82(2). 51–51. 17 indexed citations
6.
Zhou, Qianqian, et al.. (2023). Deep learning, geometric characterization and hydrodynamic modeling for assessing sewer defect impacts on urban flooding: A case study in Guangzhou, China. Journal of Environmental Management. 351. 119689–119689. 9 indexed citations
7.
Kang, Xiaoyu, et al.. (2022). Automatic Classification System of Drainage Hole Blockage Based on Convolution Neural Network Transfer Learning. Advances in Civil Engineering. 2022(1). 3 indexed citations
8.
Zhang, Jiqiao, et al.. (2022). Structural Damage Detection Using Convolutional Neural Networks Based on Modal Strain Energy and Population of Structures. International Journal of Computational Methods. 20(3). 6 indexed citations
9.
Zhou, Qianqian, Zuxiang Situ, Shuai Teng, et al.. (2022). Automatic sewer defect detection and severity quantification based on pixel-level semantic segmentation. Tunnelling and Underground Space Technology. 123. 104403–104403. 52 indexed citations
10.
Teng, Shuai, et al.. (2022). Optimal CNN-based semantic segmentation model of cutting slope images. Frontiers of Structural and Civil Engineering. 16(4). 414–433. 16 indexed citations
11.
Teng, Shuai, et al.. (2022). Structural Damage Recognition Based on Filtered Feature Selection and Convolutional Neural Network. International Journal of Structural Stability and Dynamics. 22(12). 14 indexed citations
12.
Fang, Zhuangcheng, et al.. (2021). Static behavior of grouped stud shear connectors in steel–precast UHPC composite structures containing thin full-depth slabs. Engineering Structures. 252. 113484–113484. 91 indexed citations
13.
Chen, Gongfa, et al.. (2021). DIC‐Based Operational Modal Analysis of Bridges. Advances in Civil Engineering. 2021(1). 14 indexed citations
14.
Fang, Zhuangcheng, et al.. (2020). Behavior of grouped stud shear connectors between precast high-strength concrete slabs and steel beams. Steel and Composite Structures. 34(6). 837–851. 31 indexed citations
15.
Chen, Gongfa, et al.. (2020). Homography-based measurement of bridge vibration using UAV and DIC method. Measurement. 170. 108683–108683. 68 indexed citations
16.
Teng, Shuai, et al.. (2020). Structural Damage Features Extracted by Convolutional Neural Networks from Mode Shapes. Applied Sciences. 10(12). 4247–4247. 19 indexed citations
17.
Yuan, Bingxiang, et al.. (2019). Transparent Synthetic Soil and Its Application in Modeling of Soil-Structure Interaction Using Optical System. Frontiers in Earth Science. 7. 60 indexed citations
18.
Chen, Gongfa, et al.. (2019). Numerical Analysis on Shear Behavior of Joints under Low Confining and Eccentric Loads. Advances in Civil Engineering. 2019(1). 12 indexed citations
19.
Chen, Gongfa, et al.. (2017). Numerical Analyses of Shear Behaviors of Epoxy Joints in Precast Concrete Segmental Bridges. 7(2). 67–71. 1 indexed citations
20.
Chen, Gongfa, et al.. (2016). Biomechanical Assessment for Healing Progression of Fractured Long Bones: Comparisons of Various Methods Using Beam Models. International Journal of Applied Mechanics. 8(6). 1650074–1650074. 8 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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