Special Session XIII

Reliability Statistical Modeling Methods
可靠性统计建模方法

We are honored to organize a special session on “Reliability Statistical Modeling Methods” as part of the upcoming SRSE 2024. Given the inherent reparability, redundancy incorporation, and safety imperatives associated with complex equipment and systems, reliability emerges as a pivotal concern within engineering and management domains.
Statistical modeling plays an essential role as a fundamental tool to estimate system quality or lifespan based on observed data. The objective of this session is to explore the state-of-the-art statistical methodologies and tools for reliability analysis, with practical applications in reliability engineering.
Relevant topics may include, but are not limited to: domain adaptation theory, optimal design, change point detection, and quality control.
我们很荣幸能够在即将到来的SRSE 2024会议中组织题为“可靠性统计建模方法”的专题会议。鉴于复杂设备和系统所具有的可修复性、冗余性和安全性要求，可靠性已成为工程和管理领域的关键关注点。统计建模作为一项基础工具在基于观测数据进行系统质量或寿命的估计上发挥着至关重要的作用。本次会议的目标是探讨用于可靠性分析的先进统计方法和工具，并探讨它们在可靠性工程中的实际应用。相关主题包括但不限于领域自适应理论、最优设计、变点检测、质量控制等。

Chair: Dianpeng Wang, Beijing Institute of Technology, China

Dianpeng Wang is an Associate Professor at the School of Mathematics and Statistics, Beijing Institute of Technology, and a supervisor for master’s and doctoral students. He completed his postdoctoral research at the Academy of Mathematics and Systems Science, Chinese Academy of Sciences, and has visited institutions such as the Georgia Institute of Technology and the Hong Kong University of Science and Technology. He serves as an executive director of the Beijing Big Data Association, an executive director of the Youth Statisticians Association of the National Industrial Statistics Teaching and Research Association, a director of the Design of Experiments Section of the Chinese Association for Applied Statistics, and a director of the National Industrial Statistics Teaching and Research Association. His research focuses on computer experiments, Bayesian computation, uncertainty quantification, and industrial big data. He has led several projects, including the National Natural Science Foundation of China’s Young Scientist Fund and General Program, as well as advanced star-rocket general technology projects under the State Administration of Science, Technology and Industry for National Defense. He has published numerous papers in prestigious statistical journals such as Technometrics, Journal of Quality Technology, and Statistica Sinica. (E-Mail: wdp@bit.edu.cn)

王典朋，北京理工大学数学与统计学院副教授，博士生导师。中国科学院系统与数学研究所博士后，曾先后访问佐治亚理工、香港科技大学，担任北京大数据协会常务理事、全国工业统计学教学研究会青年统计学家协会常务理事、中国现场统计研究会试验设计分会理事、全国工业统计学教学研究会理事。主要从事计算机试验设计、贝叶斯计算、不确定性量化、工业大数据等方向的研究。主持国家自然科学基金青年基金、面上项目和国家国防科技工业局先进星箭共性技术等项目多项，在Technometrics、Journal of Quality Technology、Statistica Sinica等统计学权威期刊上发表论文多篇。

Chair: Mei Han, Nanjing University of Aeronautics and Astronautics, China

Mei Han is an Associate Professor and master’s supervisor at the college of Economics and Management, Nanjing University of Aeronautics and Astronautics. She was selected for the 2024 Young Elite Scientists Sponsorship Program of Jiangsu Province. She received her bachelor’s degree in Automation from Huazhong University of Science and Technology and her PhD in Systems Engineering Management from City University of Hong Kong. Her research interests include statistical quality management in industrial engineering, computer experiment design and optimization, and applications in quality management and control. She is a director of the Industrial Engineering Section of the Operations Research Society of China, a member of the System Reliability Section of the Chinese Society of Systems Engineering, and a young member of the Reliability Section of the Operations Research Society of China. She has led two projects funded by the National Natural Science Foundation of China (one general project and one youth project) and eight other provincial and ministerial projects. Her research findings have been published in top-tier and authoritative international journals such as the Journal of Quality Technology, IISE Transactions, and Swarm and Evolutionary Computation. (E-Mail: meihan2@nuaa.edu.cn)

韩梅，南京航空航天大学经济与管理学院副教授，硕士生导师。入选江苏省2024年度青年科学家资助计划。本科毕业于华中科技大学自动化专业，博士毕业于香港城市大学系统工程与工程管理专业。研究方向包括工业工程中的统计质量管理、计算机试验设计与优化、及质量管理和控制的应用等。担任中国优选法统筹法与经济数学研究会工业工程分会理事、 中国系统工程学会系统可靠性分会委员、中国运筹学会可靠性分会青年委员。主持国家自科基金项目2项（面上项目1项和青年项目1项），主持省部级及其他项目8项，研究成果发表在《Journal of Quality Technology》、《IISE Transactions》、《Swarm and Evolutionary Computation》等国际顶级与权威学术期刊。

 Submission Portal

If you are interested in the special session, please submit your paper or abstract here
https://www.zmeeting.org/submission/srse2024 and choose special session 13.

For any questions, please mail the organizers or conference secretary srse@sciei.org.