Publications

Working papers

  • Liangliang Zhuang, Yizhong Ma, Guanqi Fang, and Ancha Xu* (2025+). “Modeling Two-Scale Degradation with Heterogeneity: A Unified Random-Effects Inverse Gaussian Framework”, IISE Transactions, under revision.

  • Liangliang Zhuang, Gauthier Barbosa*, Zhisheng Ye (2025+). “Data-Driven KNN Modeling for Mixed Data: An Optimized Weighted Distance Approach”, Applied Soft Computing, with Editor.

  • Liangliang Zhuang, Yizhong Ma, and Ancha Xu* (2025+). “Online estimation and remaining useful life prediction considering sensor degradation”, under preparation.

  • Liangliang Zhuang, Yinhong, and Ancha Xu* (2025+). “Inverse Gaussian Process for Prognostics and Health Management: Modeling, Prediction, and Decision Optimization”, under preparation.

* Corresponding author

Acadamic Talks

  • Multivariate rIG processes with common effects for degradation-based reliability prediction
    reported by Liangliang.

    • 中国现场统计研究会可靠性工程分会 2025 年学术年会, 2025.09, 陕西-延安.

  • Modeling Two-Scale Degradation with Heterogeneity: A Unified Random-Effects Inverse Gaussian Framework
    reported by Liangliang.

    • 新加坡国立大学工业系统工程与管理系, 2024.12, 新加坡.
    • 第二十一届中韩双边质量国际会议, 2025.08, 河南-洛阳.

  • Stochastic Modeling for Two-Stage and Multivariate Degradation Process
    reported by Prof. Tang, produced by Liangliang. [Slides]

    • The 6th International Conference on System Reliability and Safety Engineering (Keynote Speech), 2024.10.

  • Reparameterized Inverse Gaussian Process and Its Applications
    reported by Prof. Xu, produced by Liangliang. [Slides]

    • 北京理工大学数学与统计学院, 2024.08.

  • A Multivariate Student-t Process Model for Dependent Tail-Weighted Degradation Data
    reported by Prof. Xu, produced by Liangliang. [Slides]

    • 中国运筹学会可靠性分会学术年会, 2024.04.

  • Remaining Useful Life Prediction for Two-Phase Degradation Model Based on Reparameterized Inverse Gaussian Process
    reported by Prof. Xu, produced by Liangliang. [Slides]

    • 中国优选法统筹法与经济数学研究会工业工程分会学术交流暨学会年会, 宁夏-银川, 2025.09. (reported by Liangliang)
    • 天津大学管理与经济学部, 2024.03.
    • 北京理工大学管理与经济学院, 2024.03.
    • 苏州大学数学科学学院, 2023.11.
    • 中国运筹学会可靠性分会年会(优秀论文), 2023.12. (reported by Liangliang)

  • Prognostic Driven Predictive Maintenance Framework Based on Bayesian Deep Learning
    reported by Liangliang. [Slides]

    • 中国现场统计研究会可靠性分会学术年会, 2023.06.
    • The 4th International Conference on System Reliability and Safety Engineering (Best Student Paper Award), 2022.12.
    • 第六届全国统计学博士研究生学术论坛(二等奖), 2022.11

Other Talks

  • Research Steps and Techniques
    Seminar held by 荷兰心理学联盟 (in Chinese), 2024. Slides, Video

  • Deep learning with R for beginners
    Seminar held by 统计之都 (in Chinese), 2022. Video, Code

  • Visualization tutorial using R
    Summer Seminar (in Chinese), 2021. Video, HTML

  • R Markdown tutorial for beginners
    Self-made online courses (in Chinese), 2021. Video, HTML, Slides I, II

Adhoc Reviewer

Journals

  • Journal of Quality Technology
  • IEEE Transactions on Reliability
  • Computers & Industrial Engineering
  • Computers in Industry
  • Mechanical Systems and Signal Processing
  • Reliability Engineering and System Safety
  • Knowledge-Based Systems

Honors & Awards

  • Outstanding Graduates of Zhejiang Province (2025.03)

  • National Scholarship for PhD Students (2024.11)

  • China Scholarship Council program (2024.01 - 2025.01)

  • Best Paper at the 2023 Annual Conference of the Reliability Sub-Society of the Operations Research Society of China (2023.12)

  • Best Student Paper Award in the 4th International Conference on System Reliability and Safety Engineering (SRSE) (2022.12)

  • Second Prize of the 6th National Academic Forum for PhD Students in Statistics (2022.11)

  • Third prize in the “Obey Cup” Industrial Supply Chain Data Intelligence Innovation Competition (2022.11)

  • Outstanding Graduate of Zhejiang Province (2021.10)

  • National Scholarship for Postgraduate Students (2021.09)

  • Third Prize in National Graduate Mathematical Modeling Competition (2020, 2019)

Books