2025 The 9th International Conference on System Reliability and Safety
Turin, Italy - November 26-28, 2025

Session Keynote Lectures

 

Janet (Jing) Lin, Luleå University of Technology, Sweden

Dr. Janet (Jing) Lin is a Professor (Associate) and Docent at Luleå University of Technology, Sweden, and a recognized expert in reliability-focused engineering. She serves as Vice President of the IEEE Reliability Society, where she leads initiatives in Membership (2023–2024) and Publications (2025 onward), and is the founding Chair of the IEEE Reliability Society Joint Sweden–Norway Chapter. She was honored as the IEEE Reliability Society “Reliability Engineer of the Year” in 2024 and is an IEEE Distinguished Lecturer from IEEE WiE 2023.
Dr. Lin serves as Associate Editor for IEEE Transactions on Reliability and sits on the editorial boards of several IEEE Transactions. Her research advances reliability-focused innovation, design, operation, and maintenance engineering, with applications across transportation, energy, manufacturing, electronics, and heavy industries. She is a pioneer of Dependability-Centered Asset Management (DCAM). She earned her PhD in Management Science from Nanjing University of Science & Technology in 2008 and served as a Senior Asset Management Consultant at SKF Ltd., Co. from 2008 to 2011.

Title: The Dual Perspective of AI in Reliability: From Smart Assets to Trustworthy Systems
Abstract: Artificial Intelligence (AI) is reshaping reliability engineering from two perspectives. First, AI is a powerful tool to improve asset performance, enable predictive maintenance, and optimize lifecycle management across industries such as energy, transportation, and manufacturing. Second, AI itself must be engineered for reliability, raising critical issues of robustness, explainability, lifecycle drift, and certification in safety-critical domains.

This talk explores these dual perspectives—AI for reliability and the reliability of AI—drawing on case studies and international collaborations. It highlights current advances, open challenges, and opportunities for building trustworthy, resilient, and intelligent systems in the age of AI.

 

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