Dr. Junlin Heng is an Associate Professor at Sichuan University, specialising in structural engineering, particularly focusing on offshore wind turbine structures, digital twins, and predictive maintenance. His research interests lie in intelligent monitoring systems, corrosion-fatigue degradation, and the integration of advanced sensors with AI-driven decision-making models to improve the performance and resilience of renewable energy systems. Dr. Heng's work explores the application of multi-physics simulations, data-driven methods, and digital twin technologies to diagnose and predict the long-term degradation behaviors of offshore wind turbines. He is also interested in the development of novel control and maintenance strategies, particularly for floating offshore wind turbines, where environmental conditions present unique challenges. His current research focuses on enhancing SHM systems, improving risk-informed decision-making, and creating dynamic, real-time maintenance strategies using machine learning and multi-source data fusion. Dr. Heng has led several interdisciplinary projects, collaborating with both academic and industrial partners to develop innovative solutions for wind energy.