Qilin Li 
- (2025): A probability-based risk assessment of secondary fragments ejected from the reinforced concrete wall under close-in explosions. In: Structural Safety, v. 114 (May 2025).
- (2025): A multi-task machine learning approach for data efficient prediction of blast loading. In: Engineering Structures, v. 326 (March 2025).
- (2024): Fragment prediction of reinforced concrete wall under close-in explosion using Fragment Graph Network (FGN). In: Computers & Structures, v. 305 (December 2024).
- : 3DGEN: a framework for generating custom-made synthetic 3D datasets for civil structure health monitoring. In: Structural Health Monitoring.
- (2024): 3D displacement measurement using a single-camera and mesh deformation neural network. In: Engineering Structures, v. 318 (November 2024).
- (2024): Structural damage identification by using physics-guided residual neural networks. In: Engineering Structures, v. 318 (November 2024).
- (2024): Out-of-plane full-field vibration displacement measurement with monocular computer vision. In: Automation in Construction, v. 165 (September 2024).
- (2024): Prediction of BLEVE-induced response of road tunnel using Transformer network with modified self-attention (SAMT). In: Engineering Structures, v. 314 (September 2024).
- (2024): Advancing blast fragmentation simulation of RC slabs: A graph neural network approach. In: Engineering Structures, v. 308 (June 2024).
- (2023): Machine learning prediction of structural dynamic responses using graph neural networks. In: Computers & Structures, v. 289 (December 2023).
- (2023): A novel transformer-based semantic segmentation framework for structural condition assessment. In: Structural Health Monitoring, v. 23, n. 2 (July 2023).
- (2023): Multi‐channel response reconstruction using transformer based generative adversarial network. In: Earthquake Engineering and Structural Dynamics, v. 52, n. 11 (June 2023).
- (2023): Monocular vision based 3D vibration displacement measurement for civil engineering structures. In: Engineering Structures, v. 293 (October 2023).
- (2023): A comparative study on the most effective machine learning model for blast loading prediction: From GBDT to Transformer. In: Engineering Structures, v. 276 (February 2023).
- (2004): Pore Blockage Effects on Atrazine Adsorption in a Powdered Activated Carbon/Membrane System. II: Model Verification and Application. In: Journal of Environmental Engineering (ASCE), v. 130, n. 11 (November 2004).
- (2004): Pore Blockage Effects on Atrazine Adsorption in a Powdered Activated Carbon/Membrane System. I: Model Development. In: Journal of Environmental Engineering (ASCE), v. 130, n. 11 (November 2004).
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