w Ma Yafei, Zhou Haiyang, He Yu, Wang Lei. Multi-scale adaptive graph attention network for structural dynamic response forecasting under data scarcity. Measurement, 2026

w Peng Anyin, Ma Yafei*, Wang Lei, Zhang Jianren. Localization and automatic quantification of crack damage in steel structures using ultrasonic guided wave technology. Journal of Materials in Civil Engineering, 2026, 38(4): 04026029

w Wang Jing, Yao Haizhou, Hu Qian, Hu Jinbin, Wang Jin, Ma Yafei*. RTDSeg: Hard example sampling driven real-time concrete structural damage segmentation network. Advanced Engineering Informatics, 2026, 69: 103811

w Ma Yafei, Zhang Bachao, Huang Ke, Wang Lei. Probabilistic prediction and early warning for bridge bearing displacement using sparse variational gaussian process regression. Structural Safety, 2025, 114: 102564

w He Yu, Gao Guorong, Ma Yafei*, Huang Ke, Yu Xiaohui, Qian Kai, Wang Lei. Physics-informed Bayesian fusion framework for bridge network vulnerability integrated with a GPR surrogate model. Engineering Structures, 2025, 343: 121088

w He Yu, Ma Yafei*, Huang Ke, Wang Lei, Zhang Jianren. Abnormal data detection and recovery of sensors network based on spatiotemporal deep learning methodology, Measurement, 2024, 228: 114368

w He Yu, Ma Yafei*, Huang Ke, Wang Lei, Zhang Jianren. Digital twin Bayesian entropy framework for corrosion fatigue life prediction and calibration of bridge suspender. Reliability Engineering and System Safety, 2024, 252: 110456

w Peng Anyin, Ma Yafei*, Huang Ke, Wang Lei. Digital twin-driven framework for fatigue life prediction of welded structures considering residual stress. International Journal of Fatigue, 2024, 181: 108144

w Ma Yafei, He Yu, Wang Guodong, Wang Lei, Zhang Jianren, Lee Deuckhang. Corrosion fatigue crack growth prediction of bridge suspender wires using Bayesian gaussian process. International Journal of Fatigue, 2023, 168: 107377

w Ma Yafei, He Yu, Wang Lei, Zhang Jianren. Probabilistic reconstruction for spatiotemporal sensor data integrated with Gaussian process regression. Probabilistic Engineering Mechanics, 2022, 69: 103264