Chao Su

621 total citations · 1 hit paper
20 papers, 452 citations indexed

About

Chao Su is a scholar working on Civil and Structural Engineering, Mechanical Engineering and Genetics. According to data from OpenAlex, Chao Su has authored 20 papers receiving a total of 452 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Civil and Structural Engineering, 7 papers in Mechanical Engineering and 3 papers in Genetics. Recurrent topics in Chao Su's work include Infrastructure Maintenance and Monitoring (8 papers), Concrete Corrosion and Durability (6 papers) and Non-Destructive Testing Techniques (4 papers). Chao Su is often cited by papers focused on Infrastructure Maintenance and Monitoring (8 papers), Concrete Corrosion and Durability (6 papers) and Non-Destructive Testing Techniques (4 papers). Chao Su collaborates with scholars based in China and United Kingdom. Chao Su's co-authors include Wenjun Wang, Heng Zhang, Yijia Dong, Li Yang, Loi Lei Lai, Fuhua Zhang, Qiang Yang, Chun Sing Lai, Peng Wang and Ning Song and has published in prestigious journals such as Environmental Pollution, IEEE Access and Automation in Construction.

In The Last Decade

Chao Su

18 papers receiving 445 citations

Hit Papers

align trajectories

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.

Automatic concrete crack segmentation model based on transformer

2022 134 citations Wenjun Wang, Chao Su Automation in Construction profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Chao Su China	8	382	137	50	44	31	20	452
Maziar Jamshidi Canada	8	305 0.8×	120 0.9×	57 1.1×	45 1.0×	35 1.1×	11	370
Van-Duc Tran Vietnam	9	436 1.1×	117 0.9×	60 1.2×	68 1.5×	28 0.9×	16	533
Seungbo Shim South Korea	10	294 0.8×	73 0.5×	45 0.9×	57 1.3×	19 0.6×	25	358
Mark David Jenkins United Kingdom	11	372 1.0×	139 1.0×	52 1.0×	52 1.2×	39 1.3×	18	492
Shanglian Zhou United States	10	291 0.8×	97 0.7×	28 0.6×	40 0.9×	34 1.1×	16	372
Pang‐jo Chun Japan	12	253 0.7×	60 0.4×	28 0.6×	27 0.6×	29 0.9×	31	376
Keunyoung Jang South Korea	7	361 0.9×	89 0.6×	34 0.7×	68 1.5×	56 1.8×	11	432
Shi Qiu China	10	252 0.7×	92 0.7×	64 1.3×	35 0.8×	37 1.2×	33	366
Dihao Ai China	6	328 0.9×	78 0.6×	25 0.5×	49 1.1×	26 0.8×	10	384

Countries citing papers authored by Chao Su

Since Specialization

Citations

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

Fields of papers citing papers by Chao Su

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chao Su

This figure shows the co-authorship network connecting the top 25 collaborators of Chao Su. A scholar is included among the top collaborators of Chao Su 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 Chao Su. Chao Su 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

Su, Chao, et al.. (2025). Transformer‐based crack segmentation for concrete structures in complex scenarios. Structural Concrete. 27(1). 474–491. 1 indexed citations

Zhang, Xiaoyu, et al.. (2025). Multiscale applicability assessment of PM2.5 datasets in Chinese urban agglomerations: Accuracy, spatiotemporal variability, and uncertainty. Environmental Pollution. 383. 126810–126810. 2 indexed citations

Wang, Wenjun, et al.. (2023). A lightweight crack segmentation network based on knowledge distillation. Journal of Building Engineering. 76. 107200–107200. 36 indexed citations

Wang, Wenjun & Chao Su. (2023). Deep learning-based detection and condition classification of bridge steel bearings. Automation in Construction. 156. 105085–105085. 19 indexed citations

Li, Ruiyun, et al.. (2023). Associations between ecological diversity and rodent plague circulation in Yunnan Province, China, 1983–2020: A data-informed modelling study. PLoS neglected tropical diseases. 17(6). e0011317–e0011317.

Su, Chao, et al.. (2023). A Two-Terminal Fault Location Fusion Model of Transmission Line Based on CNN-Multi-Head-LSTM with an Attention Module. Energies. 16(4). 1827–1827. 7 indexed citations

Wang, Wenjun & Chao Su. (2022). Automatic concrete crack segmentation model based on transformer. Automation in Construction. 139. 104275–104275. 134 indexed citations breakdown →

Wang, Wenjun & Chao Su. (2022). Automatic Classification of Reinforced Concrete Bridge Defects Using the Hybrid Network. Arabian Journal for Science and Engineering. 47(4). 5187–5197. 13 indexed citations

Wang, Wenjun & Chao Su. (2021). Semi-supervised semantic segmentation network for surface crack detection. Automation in Construction. 128. 103786–103786. 88 indexed citations

10.

Su, Chao, et al.. (2020). Design Optimization of Concrete Aqueduct Structure considering Temperature Effects. Mathematical Problems in Engineering. 2020. 1–11. 6 indexed citations

11.

Su, Chao & Wenjun Wang. (2020). Concrete Cracks Detection Using Convolutional NeuralNetwork Based on Transfer Learning. Mathematical Problems in Engineering. 2020. 1–10. 57 indexed citations

12.

Wang, Wenjun & Chao Su. (2020). Convolutional Neural Network-Based Pavement Crack Segmentation Using Pyramid Attention Network. IEEE Access. 8. 206548–206558. 62 indexed citations

13.

Song, Ning, et al.. (2020). Research on Stability of Gabion Slope on Seepage-stress Coupling. IOP Conference Series Earth and Environmental Science. 585(1). 12042–12042. 2 indexed citations

14.

Su, Chao, et al.. (2020). Research on the Optimization Design of Abnormal Flip Buckets. Mathematical Problems in Engineering. 2020. 1–14. 2 indexed citations

15.

Su, Chao, et al.. (2019). Isolation and epidemiological significance of Yersinia pestis phages in indicator animals from the house mouse plague foci of Yunnan Province. Chin J Endemiol. 38(11). 861–867.

16.

Su, Chao, et al.. (2018). The Investigation and 3D Numerical Simulation of Herb Roots in Reinforcing Soil and Stabilizing Slope. KSCE Journal of Civil Engineering. 22(12). 4909–4921. 16 indexed citations

17.

Li, Tang, et al.. (2017). The community structures and species diversity of fleas in Yulong plague focus, Yunnan province.. Zhongguo meijie shengwuxue ji kongzhi zazhi. 28(3). 201–215. 1 indexed citations

18.

Su, Chao. (2013). Application of BP Neural Network in Water Quality Evaluation of Fenhe River. Journal of Shanxi University. 1 indexed citations

19.

Yang, Li, et al.. (2010). Age structure and parasites of Malayan pangolin (Manis javanica).. 14(1). 22–25. 4 indexed citations

20.

Su, Chao. (2007). Continuum topology optimization method for arch axis design of arciform aqueducts. Journal of Hohai University. 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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