Limao Zhang 
- (2023): Dual attention-based deep learning network for multi-class object semantic segmentation of tunnel point clouds. In: Automation in Construction, v. 156 (Dezember 2023).
- (2024): Digital twin enabled real-time advanced control of TBM operation using deep learning methods. In: Automation in Construction, v. 158 (Februar 2024).
- (2023): Dynamic and explainable deep learning-based risk prediction on adjacent building induced by deep excavation. In: Tunnelling and Underground Space Technology, v. 140 (Oktober 2023).
- (2023): Deep learning for large-scale point cloud segmentation in tunnels considering causal inference. In: Automation in Construction, v. 152 (August 2023).
- : Adaptively unsupervised seepage detection in tunnels from 3D point clouds. In: Structure and Infrastructure Engineering.
- (2023): Attention-enhanced sampling point cloud network (ASPCNet) for efficient 3D tunnel semantic segmentation. In: Automation in Construction, v. 146 (Februar 2023).
- (2023): Data-driven real-time advanced geological prediction in tunnel construction using a hybrid deep learning approach. In: Automation in Construction, v. 146 (Februar 2023).
- (2022): Decision-Making Based on Network Analyses of New Infrastructure Layouts. In: Buildings, v. 12, n. 7 (5 Juli 2022).
- (2022): Data-driven multi-output prediction for TBM performance during tunnel excavation: An attention-based graph convolutional network approach. In: Automation in Construction, v. 141 (September 2022).
- (2022): Building damage detection from satellite images after natural disasters on extremely imbalanced datasets. In: Automation in Construction, v. 140 (August 2022).
- (2022): Data-Driven Multiscale Modelling and Analysis of COVID-19 Spatiotemporal Evolution Using Explainable AI. In: Sustainable Cities and Society, v. 80 (Mai 2022).
- (2022): Discovering spatial-temporal patterns via complex networks in investigating COVID-19 pandemic in the United States. In: Sustainable Cities and Society, v. 77 (Februar 2022).
- (2022): Deep learning for detecting building façade elements from images considering prior knowledge. In: Automation in Construction, v. 133 (Januar 2022).
- (2021): Correlating dynamic climate conditions and socioeconomic-governmental factors to spatiotemporal spread of COVID-19 via semantic segmentation deep learning analysis. In: Sustainable Cities and Society, v. 75 (Dezember 2021).
- (2021): Discovering optimal strategies for mitigating COVID-19 spread using machine learning: Experience from Asia. In: Sustainable Cities and Society, v. 75 (Dezember 2021).
- (2021): Automated process discovery from event logs in BIM construction projects. In: Automation in Construction, v. 127 (Juli 2021).
- (2019): Computational methodologies for optimal sensor placement in structural health monitoring: A review. In: Structural Health Monitoring, v. 19, n. 4 (September 2019).
- (2021): A BIM-data mining integrated digital twin framework for advanced project management. In: Automation in Construction, v. 124 (April 2021).
- (2020): Concession period optimisation in complex projects under uncertainty: a public–private partnership perspective. In: Construction Management and Economics, v. 39, n. 2 (Oktober 2020).
- (2020): Clustering of designers based on building information modeling event logs. In: Computer-Aided Civil and Infrastructure Engineering, v. 35, n. 7 (April 2020).
- (2020): Collaborative relationship discovery in BIM project delivery: A social network analysis approach. In: Automation in Construction, v. 114 (Juni 2020).
- (2020): BIM log mining: Learning and predicting design commands. In: Automation in Construction, v. 112 (April 2020).
- (2020): Bayesian Belief Network-Based Project Complexity Measurement Considering Causal Relationships. In: Journal of Civil Engineering and Management, v. 26, n. 2 (Februar 2020).
- (2020): BIM log mining: Exploring design productivity characteristics. In: Automation in Construction, v. 109 (Januar 2020).
- (2016): BIM-based Risk Identification System in Tunnel Construction. In: Journal of Civil Engineering and Management, v. 22, n. 4 (August 2016).
- (2016): Case Study of Integrated Prefab Accommodations System for Migrant On-Site Construction Workers in China. In: Journal of Professional Issues in Engineering Education and Practice, v. 142, n. 4 (Oktober 2016).
- (2018): BIM Log Mining: Measuring Design Productivity. In: Journal of Computing in Civil Engineering, v. 32, n. 1 (Januar 2018).
- (2019): Discovering worst fire scenarios in subway stations: A simulation approach. In: Automation in Construction, v. 99 (März 2019).
- (2015): Conservation of historical buildings in tunneling environments: Case study of Wuhan metro construction in China. In: Construction and Building Materials, v. 82 (Mai 2015).
- (2018): BIM log mining: Discovering social networks. In: Automation in Construction, v. 91 (Juli 2018).
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