Biography: Dr. Bingchang Hou is affiliated with the State Key Laboratory of Mechanical Transmission for Advanced Equipment, Chongqing University, China. His research interests cover machinery fault diagnosis and prognostics as well as intelligent autonomous systems. Representative original contributions include impulsive mode decomposition, new sparsity measures (e.g., generalized Gini index), optimized weights spectrum, difference mode decomposition, etc. He was awarded the fellowship of China National Postdoctoral Program for Innovative Talents. He earned his Ph.D. in Mechanical Engineering (Industrial Engineering) from Shanghai Jiao Tong University, China. During his doctoral studies, he conducted a one-year visiting research at City University of Hong Kong, and secured the First batch of the NSFC Basic Research Program for Doctoral Students.
Dr. Hou has five several Outstanding Reviewer Awards from IEEE TIM and MSSP. He serves as an Associate Editor of IEEE Transactions on Instrumentation and Measurement, and a Youth Editorial Board Member of the Journal of Reliability Science and Engineering and Journal of Dynamics, Monitoring and Diagnostics. He was named a 2026 Emerging Leader by Measurement Science and Technology, and included in the 2025 World’s Top 2% Scientists list released by Stanford University and Elsevier.
Biography: Dr. Laihao Yang received his Ph.D. Degree in the School of Mechanical Engineering from Xi’an Jiaotong University. He was a research fellow of the Structural Dynamics & Acoustic Systems Laboratory (SDASL). He is now in the faculty of the School of Mechanical Engineering at Xi’an Jiaotong University. His research interests include nonlinear vibration modeling and analysis, data-driven structural dynamics, compressive sensing, interpretable AI, and soft robotics. He is the recipient of the first Prize of Science and Technology Award of Shaanxi Higher Education Institutions and the best paper award of CMMNO 2024. He is currently serving on the Junior Editorial Board Member of Soft Science and Robot Learning, the council member of the Professional Committee for Dynamic Testing in the Chinese Society of Vibration Engineering.
