Jiangpeng Shu

1.6k total citations · 1 hit paper
71 papers, 1.1k citations indexed

About

Jiangpeng Shu is a scholar working on Civil and Structural Engineering, Building and Construction and Geology. According to data from OpenAlex, Jiangpeng Shu has authored 71 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, 31 papers in Building and Construction and 17 papers in Geology. Recurrent topics in Jiangpeng Shu's work include Infrastructure Maintenance and Monitoring (39 papers), Structural Health Monitoring Techniques (32 papers) and Concrete Corrosion and Durability (22 papers). Jiangpeng Shu is often cited by papers focused on Infrastructure Maintenance and Monitoring (39 papers), Structural Health Monitoring Techniques (32 papers) and Concrete Corrosion and Durability (22 papers). Jiangpeng Shu collaborates with scholars based in China, Sweden and United States. Jiangpeng Shu's co-authors include Weijian Zhao, Wei Ding, Han Yang, Ke Yu, Yifan Gao, Kamyab Zandi, Mario Plos, Yunyi Liu, Ziye Zhang and Yuanfeng Duan and has published in prestigious journals such as SHILAP Revista de lepidopterología, Nano Energy and Construction and Building Materials.

In The Last Decade

Jiangpeng Shu

67 papers receiving 1.1k citations

Hit Papers

Crack detection and quantification for concrete structure... 2023 2026 2024 2023 25 50 75 100

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jiangpeng Shu China 20 816 356 205 177 98 71 1.1k
Fernando Moreu United States 18 787 1.0× 143 0.4× 269 1.3× 199 1.1× 55 0.6× 89 1.1k
José Antonio Lozano-Galant Spain 21 759 0.9× 221 0.6× 77 0.4× 208 1.2× 98 1.0× 86 1.1k
Brent Phares United States 18 1.1k 1.4× 276 0.8× 130 0.6× 182 1.0× 143 1.5× 131 1.3k
Jónatas Valença Portugal 15 754 0.9× 195 0.5× 270 1.3× 68 0.4× 47 0.5× 50 929
Geraldine S. Cheok United States 16 658 0.8× 521 1.5× 272 1.3× 82 0.5× 24 0.2× 74 1.1k
Enhui Yang China 15 1.5k 1.9× 109 0.3× 101 0.5× 409 2.3× 53 0.5× 35 1.7k
Varun Kasireddy United States 7 724 0.9× 87 0.2× 162 0.8× 145 0.8× 20 0.2× 11 839
Jinsong Zhu China 24 1.2k 1.5× 362 1.0× 36 0.2× 175 1.0× 112 1.1× 69 1.3k
José Turmo Spain 23 1.1k 1.3× 486 1.4× 53 0.3× 169 1.0× 91 0.9× 98 1.3k

Countries citing papers authored by Jiangpeng Shu

Since Specialization
Citations

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

Fields of papers citing papers by Jiangpeng Shu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiangpeng Shu

This figure shows the co-authorship network connecting the top 25 collaborators of Jiangpeng Shu. A scholar is included among the top collaborators of Jiangpeng Shu 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 Jiangpeng Shu. Jiangpeng Shu 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.
Shu, Jiangpeng, et al.. (2025). A NURBS-based approach to the generation of geometric models for complex-shaped bridge using point clouds. Engineering Structures. 335. 120324–120324. 1 indexed citations
2.
Shu, Jiangpeng, et al.. (2025). Subsurface defect area quantification of reinforced concrete structures with array ultrasound and dual-scale neural network. Journal of Building Engineering. 111. 113130–113130. 5 indexed citations
4.
Shu, Jiangpeng, et al.. (2025). Data-driven convolutional neural network model with multi-channel input framework for predicting structural displacement response. Advances in Structural Engineering. 29(6). 1047–1061.
5.
Shu, Jiangpeng, et al.. (2024). Automatic geometric digital twin of box girder bridge using a laser-scanned point cloud. Automation in Construction. 168. 105781–105781. 4 indexed citations
6.
Shu, Jiangpeng, et al.. (2024). Estimation of load-carrying capacity of cracked RC beams using 3D digital twin model integrated with point clouds and images. Engineering Structures. 310. 118126–118126. 35 indexed citations
7.
Yang, Zihan, et al.. (2024). The application of deep learning in pipeline inspection: current status and challenges. Ships and Offshore Structures. 20(7). 1016–1027. 2 indexed citations
8.
Shu, Jiangpeng, et al.. (2024). Improved Evidence Fusion Theory for the Safety Assessment of Prestressed Concrete Bridges. Buildings. 14(4). 1144–1144. 3 indexed citations
9.
Shu, Jiangpeng, et al.. (2024). TransFrameNet: A transformer-based approach for generalized seismic performance prediction of building structures. Journal of Building Engineering. 96. 110628–110628. 5 indexed citations
10.
Shu, Jiangpeng, et al.. (2023). Point cloud-based dimensional quality assessment of precast concrete components using deep learning. Journal of Building Engineering. 70. 106391–106391. 39 indexed citations
11.
Jiang, Yu, Jiangpeng Shu, Jun Ye, & Weijian Zhao. (2023). Virtual trail assembly of prefabricated structures based on point cloud and BIM. Automation in Construction. 155. 105049–105049. 18 indexed citations
12.
Shu, Jiangpeng, et al.. (2023). Experimental study of the influence of inclined pre-cracks on shear behavior of RC beams without transverse reinforcement. Engineering Structures. 299. 117133–117133. 7 indexed citations
13.
Gao, Yifan, et al.. (2023). Polyhedron-bounded collision checks for robotic assembly of structural components. Automation in Construction. 152. 104904–104904. 5 indexed citations
14.
Ding, Wei, Han Yang, Ke Yu, & Jiangpeng Shu. (2023). Crack detection and quantification for concrete structures using UAV and transformer. Automation in Construction. 152. 104929–104929. 115 indexed citations breakdown →
16.
Liu, Gaoyang, Wei Ding, Jiangpeng Shu, Alfred Strauß, & Yuanfeng Duan. (2023). Two-Stream Boundary-Aware Neural Network for Concrete Crack Segmentation and Quantification. Structural Control and Health Monitoring. 2023. 1–17. 15 indexed citations
17.
Zhang, Zhicheng, et al.. (2023). A Binocular Vision-Based Crack Detection and Measurement Method Incorporating Semantic Segmentation. Sensors. 24(1). 3–3. 2 indexed citations
18.
Yang, Yuanzhang, Jiangpeng Shu, Wei‐Jiang Zhao, & John Orr. (2021). Shear design method for non-prismatic concrete beams reinforced using W-FRP. Structures. 30. 667–677. 1 indexed citations
19.
Shu, Jiangpeng. (2015). Structural Analysis of Existing RC Bridge Deck Slabs Structural Analysis of Existing RC Bridge Deck Slabs. Chalmers Research (Chalmers University of Technology). 4 indexed citations
20.
Shu, Jiangpeng, et al.. (2015). Punching Capacity of a Reinforced Concrete Bridge Deck Slab Loaded to Failure. KTH Publication Database DiVA (KTH Royal Institute of Technology). 6 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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