Shuai Teng

1.7k total citations
72 papers, 1.1k citations indexed

About

Shuai Teng is a scholar working on Civil and Structural Engineering, Mechanical Engineering and Environmental Engineering. According to data from OpenAlex, Shuai Teng has authored 72 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Civil and Structural Engineering, 11 papers in Mechanical Engineering and 8 papers in Environmental Engineering. Recurrent topics in Shuai Teng's work include Infrastructure Maintenance and Monitoring (43 papers), Structural Health Monitoring Techniques (23 papers) and Concrete Corrosion and Durability (18 papers). Shuai Teng is often cited by papers focused on Infrastructure Maintenance and Monitoring (43 papers), Structural Health Monitoring Techniques (23 papers) and Concrete Corrosion and Durability (18 papers). Shuai Teng collaborates with scholars based in China, Singapore and France. Shuai Teng's co-authors include Gongfa Chen, Gongfa Chen, Cheng Li, Zongchao Liu, Zuxiang Situ, Qianqian Zhou, Fangsen Cui, Gen Liu, Jiqiao Zhang and Xiaoli Sun and has published in prestigious journals such as The Journal of Chemical Physics, SHILAP Revista de lepidopterología and Journal of Cleaner Production.

In The Last Decade

Shuai Teng

69 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shuai Teng China	21	781	202	132	116	110	72	1.1k
Chul Min Yeum United States	15	736 0.9×	202 1.0×	208 1.6×	85 0.7×	118 1.1×	37	1.0k
Weidong Wang China	18	456 0.6×	192 1.0×	65 0.5×	90 0.8×	68 0.6×	81	1.1k
Gongfa Chen China	19	783 1.0×	119 0.6×	141 1.1×	52 0.4×	91 0.8×	44	1.0k
Peixin Shi China	22	965 1.2×	124 0.6×	89 0.7×	74 0.6×	86 0.8×	75	1.4k
Mayank Mishra India	21	837 1.1×	152 0.8×	151 1.1×	47 0.4×	44 0.4×	44	1.3k
Qiubing Ren China	21	927 1.2×	151 0.7×	128 1.0×	31 0.3×	54 0.5×	57	1.3k
Yongmin Yang China	23	889 1.1×	302 1.5×	116 0.9×	64 0.6×	67 0.6×	118	1.5k
Tom Iseley United States	20	1.0k 1.3×	362 1.8×	131 1.0×	61 0.5×	90 0.8×	45	1.5k
Pang‐jo Chun Japan	15	749 1.0×	152 0.8×	66 0.5×	54 0.5×	102 0.9×	47	922

Countries citing papers authored by Shuai Teng

Since Specialization

Citations

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

Fields of papers citing papers by Shuai Teng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuai Teng

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

All Works

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20 of 20 papers shown

Teng, Shuai, Airong Liu, Jiyang Fu, et al.. (2024). Review of intelligent detection and health assessment of underwater structures. Engineering Structures. 308. 117958–117958. 32 indexed citations

Teng, Shuai, et al.. (2024). Automated detection of underwater cracks based on fusion of optical and texture information. Engineering Structures. 315. 118515–118515. 8 indexed citations

Teng, Shuai, et al.. (2024). Unsupervised learning method for underwater concrete crack image enhancement and augmentation based on cross domain translation strategy. Engineering Applications of Artificial Intelligence. 136. 108884–108884. 8 indexed citations

Teng, Shuai, et al.. (2024). Automatic Road Crack Detection Using Convolutional Neural Network Based on Semi-Supervised Learning. 9(4). 69–82. 1 indexed citations

Teng, Shuai, Airong Liu, Zuxiang Situ, et al.. (2024). Plug-and-play method for segmenting concrete bridge cracks using the segment anything model with a fractal dimension matrix prompt. Automation in Construction. 170. 105906–105906. 5 indexed citations

Teng, Shuai, et al.. (2024). Prediction of stability of a slope with weak layers using convolutional neural networks. Natural Hazards. 120(13). 12081–12105. 1 indexed citations

Situ, Zuxiang, et al.. (2024). Attention-based deep learning framework for urban flood damage and risk assessment with improved flood prediction and land use segmentation. International Journal of Disaster Risk Reduction. 116. 105165–105165. 5 indexed citations

Teng, Shuai, et al.. (2023). Bridge progressive damage detection using unsupervised learning and self-attention mechanism. Engineering Structures. 301. 117278–117278. 15 indexed citations

Teng, Shuai, et al.. (2023). Pollutant inhibition in an extreme ultraviolet lithography machine by dynamic gas lock. Journal of Cleaner Production. 430. 139664–139664. 6 indexed citations

10.

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

11.

Yang, Xiaomei, Miao Hu, Xin Chen, et al.. (2023). Predicting Models for Local Sedimentary Basin Effect Using a Convolutional Neural Network. Applied Sciences. 13(16). 9128–9128. 1 indexed citations

12.

Zhang, Jiqiao, et al.. (2022). Structural damage detection based on decision-level fusion with multi-vibration signals. Measurement Science and Technology. 33(10). 105112–105112. 9 indexed citations

13.

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

14.

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

15.

Teng, Shuai, et al.. (2022). Improved YOLOv3-Based Bridge Surface Defect Detection by Combining High- and Low-Resolution Feature Images. Buildings. 12(8). 1225–1225. 46 indexed citations

16.

Zhang, Fu, et al.. (2021). Model construction for field operation machinery selection and configuration in wheat-maize double cropping system. International journal of agricultural and biological engineering. 14(4). 82–89. 1 indexed citations

17.

Zhang, Fu, et al.. (2020). Design of bionic goat quadruped robot mechanism and walking gait planning.. International journal of agricultural and biological engineering. 13(5). 32–39. 1 indexed citations

18.

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

19.

Zhang, Fu, et al.. (2019). Development of agricultural bionic four-legged robot: Effect of head movement adjustment on the stability of goats. International journal of agricultural and biological engineering. 12(4). 10–15. 1 indexed citations

20.

Tan, Kang Hai, et al.. (1997). A STRUT-AND-TIE MODEL FOR DEEP BEAMS SUBJECTED TO COMBINED TOP-AND-BOTTOM LOADING. The Structural engineer. 75(13). 16 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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