Yinghao Zhao 
- (2023): Parallel convolutional neural network toward high efficiency and robust structural damage identification. In: Structural Health Monitoring, v. 22, n. 6 (April 2023).
- (2023): Experimental study on vertical temperature distribution of the two-layer smoke flow in tunnel during construction. In: Tunnelling and Underground Space Technology, v. 136 (Juni 2023).
- (2022): A Deep Learning-based Method for Automatic Abnormal Data Detection:Case Study for Bridge Structural Health Monitoring. In: International Journal of Structural Stability and Dynamics, v. 23, n. 11 (Dezember 2022).
- (2022): Autonomous surface crack identification of concrete structures based on an improved one-stage object detection algorithm. In: Engineering Structures, v. 272 (Dezember 2022).
- (2022): Spatial-temporal prediction of the environmental conditions inside an urban road tunnel during an incident scenario. In: Building and Environment, v. 212 (März 2022).
- (2021): Progressive-models method for evaluating interactive stability of steel box girders for bridges – Extension of progressive collapse method in ship structures. In: Structures, v. 33 (Oktober 2021).
- (2020): A Novel Artificial Bee Colony Algorithm for Structural Damage Detection. In: Advances in Civil Engineering, v. 2020 (Januar 2020).
- (2019): Deterministic snap-through buckling and energy trapping in axially-loaded notched strips for compliant building blocks. In: Smart Materials and Structures, v. 29, n. 2 (Dezember 2019).
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