2024

  • 01-Sep-2024: The paper “Multivariate reparameterized inverse Gaussian processes with common effects for degradation-based reliability prediction” authored by Liangliang Zhuang, Ancha Xu*, Guanqi Fang, and Yincai Tang, has been accepted for publication by Journal of Quality Technology.

  • 30-Jul-2024: The paper “A Multivariate Student-t process model for dependent tail-weighted degradation data” authored by Ancha Xu, Guanqi Fang and Liangliang Zhuang*, has been accepted for publication by IISE Transactions.

  • 07-Jul-2024: My Google Scholar citation count has reached 100. Congratulations to myself!

  • 23-Jun-2024: The paper “Remaining useful life prediction for two-phase degradation model based on reparameterized inverse Gaussian process” authored by Liangliang Zhuang, Ancha Xu*, Yijun Wang and Yincai Tang has been accepted for publication by European Journal of Operational Research.

  • Feb-2024: Our paper “A prognostic driven predictive maintenance framework based on Bayesian deep learning” has become a hot paper!

2023

  • Dec-2023: I attended The 2023 Annual Meeting of the Reliability Branch of the Chinese Operations Research Society during 11 - 12 Dec 2023, and presented the paper “Remaining useful life prediction for two-phase degradation model based on reparametrized inverse Gaussian process” by Liangliang Zhuang. The paper has received the Excellent Paper Award.

  • Jul-2023: Received funding from the China National Science Foundation and I plan to visit National University of Singapore for one year (Jan 2024 - Jan 2025).

2022

  • Dec-2022: I attended The 4th International Conference on System Reliability and Safety Engineering (online) during 15 - 18 Dec 2022, and presented the paper “A prognostic driven predictive maintenance framework based on Bayesian deep learning” by Liangliang Zhuang, Ancha Xu*, and Xiao-Lin Wang*. The paper has received the Best Student Paper Award.

  • Nov-2022: I attended The 6th Doctoral Forum on Statistics (online) during 12 - 13 Nov 2022, and presented the paper “A prognostic driven predictive maintenance framework based on Bayesian deep learning” by Liangliang Zhuang, Ancha Xu, and Xiao-Lin Wang. The paper has received the Best Student Paper Award.