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1. Yu W, Shu J* , Yang Z, Ding H, Zeng W, Bai Y. Deep Learning-Based Pipe Segmentation and Geometric Reconstruction from Poorly Scanned Point Clouds Using BIM-Driven Data Alignment, Automation in Construction , 2025, 173, 106071 (JCR Q1, IF = 10.51)
2. Shu J , Yu H, Liu G*, Duan Y, Hu H, Zhang H. DF-CDM: Conditional diffusion model with data fusion for bridge dynamic response reconstruction, Mechanical Systems and Signal Processing , 2025, 222, 111783. (JCR Q1, IF = 8.934)
3. Xia Z, Shu J *, Ding W, Gao Y, Duan Y, Debono C, Prakash G, Seychell D, Borg R. Complete-Coverage Path Planning for Surface Inspection of Cable-Stayed Bridge Tower Based on BIM and Climbing Robots, Computer-Aided Civil and Infrastructure Engineering , 2025, 1-23, 13469.
4. Shu J* , Xia Z, Gao Y. BIM-based trajectory planning for unmanned aerial vehicle-enabled box girder bridge inspection, Remote Sensing , 2025, 17(4), 682
5. Shu J , Yang H, Liu G, Yu H, Ning Y, Bairan J. Post-earthquake inspection of high-speed railway viaducts with multi-scale task interaction deep learning strategy. Advances in Structural Engineering . 2025; 28(4), 674-689
6. 舒江鹏 , 陈思民, 张从广, 王海龙*. 基于自适应改进LK光流算法的结构位移视觉测量技术在复杂环境下的性能研究， 中国公路学报 ，2025, 1-11
7. 杨涵, 徐庆凯, 章金勇, 蒋友, 于泓川, 舒江鹏 *, 徐声亮. 基于自适应改进LK光流算法的结构位移视觉测量技术在复杂环境下的性能研究， 东南大学学报(自然科学版) ，2025, 1-12
8. Shu J , Zhang X, Li W, Zeng Z, Zhang H, Duan Y*. Point cloud and machine learning-based automated recognition and measurement of corrugated pipes and rebars for large precast concrete beams, Automation in Construction , 2024, 165, 105493. (JCR Q1, IF = 10.51)
9. Gao Y, Shu J* , Xia Z, Luo Y. From muscular to dexterous: A systematic review to understand the robotic taxonomy in construction and effectiveness, Journal of Field Robotics , 2024, rob.22409 , (JCR Q2, IF = 8.34)
10. Zhang C, Shu J* , Zhang H, Ning Y, Yu Y. Estimation of load-carrying capacity of cracked RC beams using 3D digital twin model integrated with point clouds and images, Engineering Structures , 2024, 310, 118126. (JCR Q1, IF = 5.58)
11. Yang Z, Zhang Y, Bai Y*, Shu J . The application of deep learning in pipeline inspection: current status and challenges. Ships and Offshore Structures , 2024, 1–12.
12. Shu J , Yu H, Liu G*, Yang H, Guo W. Chinyong P, Strauss A, Hao H. Proposing an inherently interpretable machine learning model for shear strength prediction of reinforced concrete beams with stirrups, Case Study in Construction Materials , 2024, 20, e03350.
13. Jin Z, Chen Gu, Niu Y, Zhang C, Zhang X, Shu J* . Variational mode decomposition-based multirate data-fusion framework for estimating structural dynamic displacement by integrating vision- and acceleration-based measurements, Mechanical Systems and Signal Processing , 2024, 211, 11252. (JCR Q1, IF = 8.934)
14. Yang H, Shu J* , Li S, Duan Y. Ultrasonic array tomography-oriented subsurface crack recognition and cross-section image reconstruction of reinforced concrete structure using deep neural networks, Journal of Building Engineering , 2024, 82, 108219. (JCR Q1, IF = 7.144）
15. Yang J, Shu J* , Li J, Yu K, Zandi K, Bai Y. Experimental study of the influence of inclined pre-cracks on shear behavior of RC beams without transverse reinforcement, Engineering Structures , 2024, 299, 117133. (JCR Q1, IF = 5.58)
16. 丁威, 夏哲, 舒江鹏* , 叶建龙, 项贻强. 基于负压吸附爬壁机器人和Transformer的混凝土桥塔裂缝识别检测[J]. 中国公路学报 : 2024, 37(02): 53-64.
17. 杨涵, 李斯涵, 舒江鹏* , 许彩娥, 宁英杰, 叶建龙. 基于阵列超声和特征融合神经网络的钢筋混凝土结构内部裂缝检测. 建筑结构学报 : 2024, 45(07): 1-12
18. 杨子涵, 舒江鹏* , 杨静滢, 李俊, 白勇. 基于DIC技术的钢筋混凝土梁剪切裂缝自动提取与量化方法[J/OL]. 工程力学 :1-14.
19. Ding W, Yang H, Yu K, Shu J.* , Crack detection and quantification for concrete structures using UAV and transformer, Automation in Construction , 2023, 152, 104929. (JCR Q1, IF = 10.51)
20. Shu J , Yu H, Liu G*, Yang H, Chen Y, Duan Y. BO-Stacking: A Novel Shear Strength Prediction Model of RC Beams with Stirrups Based on Bayesian Optimization and Model Stacking, Structures , 2023, 58, 105593
21. Liu G, Ding W, Shu J* , Strauss A, Duan Y. Two-stream boundary-aware neural network for concrete crack segmentation and quantification, Structural Control and Health Monitoring , 2023, 3301106. (JCR Q1, IF = 6.06)
22. Gao Y, Shu J* , Xiao W, Jin Z., Polyhedron-bounded collision checks for robotic assembly of structural components, Automation in Construction , 2023, 152, 104904. (JCR Q1, IF = 10.51)
23. Jiang Y, Shu J , Ye J, Zhao W*. Virtual trail assembly of prefabricated structures based on point cloud and BIM, Automation in Construction , 2023, 155, 105049. (JCR Q1, IF = 10.51)
24. Shu J , Zhang C, Chen X, Niu Y*. Model-informed deep learning strategy with vision measurement for damage identification of truss structures, Mechanical Systems and Signal Processing , 2023, 196, 110327. (JCR Q1, IF = 8.934)
25. Shu J , Zhang C, Gao Y, Niu Y*. A multi-task learning-based automatic blind identification procedure for operational modal analysis, Mechanical Systems and Signal Processing , 2023, 187: 109959. (JCR Q1, IF = 8.934)
26. Shu J , Li W, Zhang C, Gao Y*, Xiang Y, Ma L. Point cloud-based dimensional quality assessment of precast concrete components using deep learning, Journal of Building Engineering , 2023, 70: 106391. (JCR Q1, IF = 7.144)
27. Niu Y, Li J, Zhou S, Liu G, Xiang Y, Zhang H, Shu J* . Dynamic displacement estimation and modal analysis of long-span bridges integrating multi-GNSS and acceleration measurements. Journal of Infrastructure Preservation and Resilience , 2023, 4:9.
28. 周姝康,丁威, 金振奋, 俞珂, 张鹤, 舒江鹏 *. 基于三维点云重建的混凝土结构裂缝定位与追踪. 建筑科学与工程学报 , 2023, 1-9.
29. 叶建龙, 丁威, 杨涵, 周炯, 舒江鹏* . 基于深度学习的路桥表观病害检测与评估. 公路 ，2023,68(10),312-319
30. Shu J , Li W, Gao Y*. Collision-free trajectory planning for robotic assembly of lightweight structures, Automation in Construction , 2022: 104520. (JCR Q1, IF = 10.51)
31. Shu J , Ding W*, Zhang J, Lin F, Duan Y. Continual-learning-based framework for structural damage recognition, Structural Control and Health Monitoring , 2022, DOI: 10.1002/stc.3093. (JCR Q1, IF = 6.06 封面论文)
32. Shu J , Zhang C*, Yu K, Shooshtarian M, Liang P. IFC-based semantic modeling of damaged RC beams using 3D point clouds. Structural Concrete , 2022, 1-12. (JCR Q2, IF = 3.10)
33. Gao Y, Meng J, Shu J* , Liu Y. BIM-based task and motion planning prototype for robotic assembly of COVID-19 hospitalisation light weight structures. Automation in Construction , 2022, 140: 104370. (JCR Q1, IF = 10.51)
34. Zhao W, Liu Y, Zhang J, Shao Y, Shu J* . Automatic pixel‐level crack detection and evaluation of concrete structures using deep learning, Structural Control and Health Monitoring , 2022, 29, e2981. (JCR Q1, IF = 6.06 封面论文)
35. Shu, J , Li, J, Zhang, J, Zhao, W, Duan, Y, Zhang, Z*. An active learning method with difficulty learning mechanism for crack detection, Smart Structures and Systems , 2022, 39(1), 53-62. (JCR Q1, IF = 4.58
36. Zhao W, Jiang Y, Liu Y, Shu J* . Automated recognition and measurement based on three-dimensional point clouds to connect precast concrete components. Automation in Construction , 2022, 133: 104000. (JCR Q1, IF = 10.51)
37. Liu, G, Niu, Y, Zhao, W, Duan, Y, Shu, J *. Data anomaly detection for structural health monitoring using a combination network of GANomaly and CNN, Smart Structures and Systems , 2022, 39(1), 195-206. (JCR Q1, IF = 4.58)
38. Zhang C, Shu J* , Shao Y, Zhao W. Automated generation of FE models of cracked RC beams based on 3D point clouds and 2D images. Journal of Civil Structural Health Monitoring , 2022, 12: 29-46. (JCR Q2, IF = 3.33)
39. 高一帆， 舒江鹏* ，俞珂，金振奋. 基于BIM可视化编程的轻型应急结构机器人智能建造研究, 建筑结构学报 ，2022, 43(S1)，294-306.
40. 舒江鹏 ，李俊，马亥波，段元锋 . 基于特征金字塔网络的超大尺寸图像的裂缝识别检测方法， 土木与环境工程学报（中英文） ，2022，44(3)，29-36.
41. 丁威,马亥波, 舒江鹏* ,NIZHEGORODTSEV Denis V,叶建龙.基于残差网络的混凝土结构病害分类识别研. 建筑科学与工程学报 ,2022,39(04):127-136.
42. Tao Y, Zhao W*, Shu J , Yang Y. Nonlinear finite-element analysis of the seismic behavior of RC column–steel beam connections with shear failure mode. Journal of Structural Engineering ASCE , 2021, 147(10): 04021160. (JCR Q2, IF = 3.85)
43. Yu, K, Zhang, C, Shooshtarian, M, Zhao, W, Shu, J *. Automated finite element modeling and analysis of cracked reinforced concrete beams from three dimensional point cloud. Structural Concrete . 2021; 22: 3213– 3227. (JCR Q2, IF = 3.10)
44. Yang Y, Shu J* , Zhao W, Orr J. Shear design method for non-prismatic concrete beams reinforced using. Structures , 2021, 30: 667–677. (JCR Q2, IF = 4.01)
45. Niu Y, Ye Y, Shu J* , Zhao W, Duan Y. Identifying modal parameters of a multi-span bridge based on high-rate GNSS–RTK measurement using the CEEMD–RDT approach. Journal of Bridge Engineering, ASCE , 2021, 26(8): 04021049. (JCR Q2, IF = 3.38)
46. Niu Y, Ye Y, Zhao W, Shu J* . Dynamic monitoring and data analysis of a long-span arch bridge based on high-rate GNSS-RTK measurement combining CF-CEEMD method. Journal of Civil Structural Health Monitoring , 2020, 11: 35–48. (JCR Q2, IF = 3.33)
47. 丁威，俞珂， 舒江鹏 * . 基于深度学习和无人机的混凝土结构裂缝检测方法， 土木工程学报 ，2021，54（S1）,1-12.
48. Shu J* , Bagge N, Nilimaa J. Field destructive testing of a reinforced concrete bridge deck slab. Journal of Bridge Engineering, ASCE , 2020, 25(9), 04020067. (JCR Q2, IF = 3.38)
49. Zandi K, Ransom E H, Topac T, Chen R, Beniwal S, Blomfors M, Shu J , Chang F-K. A framework for digital twin of civil infrastructure-challenges & opportunities// Structural Health Monitoring 2019 .
50. Shu J* , Plos M, Zandi K, Ashraf A. Distribution of shear force: A multi-level assessment of a cantilever RC slab. Engineering Structures , 2019, 190: 345–359. (JCR Q1, IF = 5.58)
51. Shu J* , Honfi D, Plos M, Zandi K, Magnusson J. Assessment of a cantilever bridge deck slab using multi-level assessment strategy and decision support framework. Engineering Structures , 2019, 200:109600. (JCR Q1, IF = 5.58)
52. Shu J* . Shear assessment of a reinforced concrete bridge deck slab according to level-of-approximation approach. Structural Concrete , 2018, 18: 1838–1850. (JCR Q2, IF = 3.10)
53. Shu J* , Bagge N, Plos M, Johansson M, Yang Y, Zandi K. Shear capacity of a RC bridge deck slab: comparison between multilevel assessment and field test. Journal of Structural Engineering, ASCE , 2018, 144(7): 04018081. (JCR Q2, IF = 3.85)
54. Shu J* , Belletti B, Muttoni A, Scolari M, Plos M. Internal force distribution in RC slabs subjected to punching shear. Engineering Structures , 2017, 153: 766–781. (JCR Q1, IF = 5.58)
55. Shu J* , Plos M, Johansson M, Zandi K, Nilenius F. Prediction of punching behaviour of RC slabs using continuum non-linear FE analysis. Engineering Structures , 2016, 125, 15-25. (JCR Q1, IF = 5.58)
56. Plos M, Shu J* , Zandi K, Lundgren K. A multi-level structural assessment strategy for reinforced concrete bridge deck slabs. Structure and Infrastructure Engineering , 2016, 13(2): 223–241. (JCR Q1, IF = 3.00)
57. Shu J* , Fall D, Plos M, Zandi K, Lundgren K. Development of modelling strategies for two-way RC slabs. Engineering Structures , 2015, 101: 439–449. (JCR Q1, IF = 5.58)
58. Shu J* , Plos M, Zandi K. A Multi-level Structural Assessment Proposal for Reinforced Concrete Bridge Deck Slabs. Nordic Concrete Research , 2015, 53(2): 53–56.
59. Bagge N*, Shu J , Plos M, Elfgren L. Punching Capacity of a Reinforced Concrete Bridge Deck Slab Loaded to Failure. Nordic Concrete Research , 2015, 53(2): 57–60.
60. Shu J* . Structural Analysis of Existing RC Bridge Deck Slabs. Nordic Concrete Research , 2015, 50(2): 453–456.
61. Fall D, Shu J* , Rempling R, Lundgren K, Zandi K. Two-way slabs: Experimental investigation of load redistributions in steel fibre reinforced concrete. Engineering Structures , 2014, 80: 61–74. (JCR Q1, IF = 5.58)
62. Shu J* , Zhang Z, Gonzalez I, Karoumi R. The application of a damage detection method using Artificial Neural Network and train-induced vibrations on a simplified railway bridge model. Engineering Structures , 2013, 52: 408–421. (JCR Q1, IF = 5.58)
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