Degradation Modeling
Inverse Gaussian processes, multivariate degradation, two-phase and two-scale reliability models.
Liangliang Zhuang
Seeking knowledge, leading with courage.
Reliability
Statistics
Bayesian
Degradation
Postdoc
PHM
RUL
Optimization
Research
Predictive Maintenance
Remaining useful life prediction, sensor degradation, Bayesian deep learning, and PHM workflows.
Bayesian & AI Systems
Hierarchical Bayesian inference, adaptive sampling, federated learning, and data-driven optimization.
Selected papers
Modeling two-scale degradation with heterogeneity: A unified random-effects inverse Gaussian framework
Liangliang Zhuang, Yizhong Ma, Guanqi Fang, and Ancha Xu*. IISE Transactions, 2026.
From Statistical Modeling to AI-Integrated Inverse Gaussian Process: A Comprehensive Review for Prognostics and Health Management
Liangliang Zhuang, Yizhong Ma, Jianjun Wang, Rong Pan, and Ancha Xu*. Engineering Management, 2026, 13(1): 65.
Multivariate reparameterized inverse Gaussian processes with common effects for degradation-based reliability prediction
Liangliang Zhuang, Ancha Xu*, Guanqi Fang, and Yincai Tang. Journal of Quality Technology, 57(1): 51-67.
Recent updates
Presented at the ZJUI Young Scholars Development Forum in Haining.
Presented at the ECNU seminar on reliability statistics.
Presented at the 2026 ORSC Reliability Branch Annual Conference.
在 ZJUI 青年学者发展论坛作学术报告。
在华东师范大学复杂系统可靠性研讨会作报告。
在中国运筹学会可靠性分会 2026 年学术年会作报告。
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