Qiuzhuang Sun

Qiuzhuang Sun is a Lecturer in the School of Mathematics and Statistics at the University of Sydney. His research focuses on data-driven decision-making, industrial statistics, and reliability engineering, with applications in healthcare, transportation, and sustainable urban systems.

• Alma Mater: Joint B.Eng. in Industrial Engineering and Computer Science from Shanghai Jiao Tong University; Ph.D. in Industrial Systems Engineering from National University of Singapore

His research interests include:

• Data-Driven Decision-Making for healthcare, emergency response, and preventive maintenance
• Applied data science and machine learning for transportation data, clinical data, and megacity sustainability
• Reliability engineering with emphasis on anomaly detection, degradation modeling, and prognostic health management

Recent publications highlight advancements in degradation modeling, robust optimization, and healthcare system design, reflecting interdisciplinary collaborations in industrial engineering, statistics, and biomedical research. His work aligns with the Faculty of Science's research strengths in Data and Decisions, Precision Health, and Sustainable Systems.

Scientific accolades include:

• Finalist, IISE Data Analytics & Information Systems Case Study Competition (2024)
• First Place, INFORMS Blue Summit Supplies Data Mining Challenge (2023)
• Best Student Paper Award, INFORMS Society on Location Analysis (2023)
• Best Paper Award, INFORMS Conference on Quality, Statistics, and Reliability (2023)
• Winner, INFORMS QSR Industrial Data Challenge Competition (2022)
• ISE Magazine Featured Article (2020)
• Excellent Paper Award, Operations Research Society of China Reliability Chapter (2019)

He supervises students in projects related to reliability engineering and data-driven decision-making. His work integrates statistical modeling, machine learning, and industrial systems optimization.