Modeling and Risk
This session discusses several modeling techniques in risk management of modern
industrial systems. The talks in this session illustrate state-of-the-art
methodology to solve challenging statistical and operations research problems,
which have a wide application in power systems, communication systems, and
Related topics:Reliability assessment, lifetime data analysis, statistical inference, queueing theory
Jiaxiang Cai received the B.E. degree in hydraulic engineering in 2012 and the M.S. degree in environmental science and engineering in 2015, both from Tsinghua University. He received the Ph.D. degree in industrial systems engineering and management in 2021 from National University of Singapore (NUS). He is currently a Research Fellow at the Department of Industrial Systems Engineering and Management, NUS. His research interests include reliability engineering and industrial statistics, and has several works published in IEEE Transactions on Industrial Informatics, Journal of Quality Technology, and IISE Transactions, among others. (Mail: email@example.com)
Xingchen Liu received the B.S. degree in measurement, control technology, and instrument from Hunan University in 2014, and the M.S. degree in instrument science and technology from University of Science and Technology of China in 2017. He is expected to obtain the Ph.D. degree in Industrial Systems Engineering and Management from National University of Singapore in December 2021. He is currently a Research Assistant at the City University of Hong Kong. His research interests include data mining and prognostics and health management.
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