As a dedicated researcher in intelligent manufacturing systems, I am enthusiastic to engage with the Hong Kong Laureate Forum’s interdisciplinary ecosystem, where cutting-edge innovation converges with sustainable industrial transformation. My expertise lies in advancing condition monitoring and predictive fault diagnosis methodologies for high-stakes mechanical systems, particularly aerospace equipment—an area that directly aligns with the Forum’s commitment to technological excellence and global sustainability.

Throughout my research career, I spearheaded multidisciplinary projects aimed at optimizing equipment reliability through AI-driven diagnostics. These endeavors have sharpened my ability to bridge theoretical frameworks with real-world applications, a competency I aspire to refine through dynamic exchanges with global laureates and peers at the Forum.

The Forum’s vision of translating scientific breakthroughs into societal value deeply resonates with my ambition to pioneer intelligent manufacturing solutions that enhance industrial safety and efficiency. By joining this collaborative platform, I aim to share my innovations in non-invasive monitoring techniques, absorb transformative insights from diverse disciplines, and cultivate partnerships that transcend traditional boundaries. I am committed to leveraging this opportunity to not only advance my academic trajectory but also contribute meaningfully to the global scientific community’s pursuit of sustainable technological progress.

My current research work covers a range of issues: machine condition monitoring, signal processing, deep learning and computer vision. Currently, I am interested in various deep-learning-based approaches and their applications to condition monitoring and fault diagnosis.I have authored or co-authored over 40 SCI-indexed papers, including 21 as the first author and 10 as the corresponding author. According to Google Scholar, my publications have received over 1,500 citations and my H-index is 23. From 2023 to 2024, I was listed among the world's top 2% scientists in the ranking published by Elsevier and Stanford University.