Our PhD Students

My PhD research revolves around the development of innovative methods that incorporate uncertainty considerations in predicting the remaining useful life of complex systems. The primary objective is to propose a comprehensive framework that enables existing methods, lacking the ability to quantify uncertainty, to effectively capture and quantify uncertainty. Simultaneously, for methods capable of quantifying uncertainty, the aim is to refine and simplify the approaches to ensure their practical applicability in real-world scenarios, while enhancing prediction accuracy. Furthermore, a key focus of the research is addressing the challenge of uncertainty propagation in remaining useful life prediction. This entails considering diverse system structures and the intricate interactions between components, allowing for a comprehensive understanding of how uncertainty propagates from the component level to the system level. This holistic approach ensures a more robust and accurate prediction of the remaining useful life. By addressing these critical aspects, my research aims to contribute to the field by providing novel methods that not only enable the quantification of uncertainty but also improve the applicability and accuracy of remaining useful life prediction models for complex systems.