Dr. Xufan Wang received his Ph.D. and M.S. degrees in Electrical Engineering from the School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China, and his B.S. degree in Mechanical and Electrical Engineering from the School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou, China. His research interests include pantograph–catenary interaction in electrified railways, advanced technologies for 400 km/h high-speed railways, applications of artificial intelligence in electrified railways, and high-speed train dynamics. He has published 19 SCIE-indexed papers. Representative publications include “A time-frequency dual-domain deep learning approach for high-speed pantograph-catenary dynamic performance prediction” and “Koopman Neural Operator-based surrogate modelling for high-frequency dynamics of high-speed rail pantographs” in Mechanical Systems and Signal Processing, and “Assessment of Current Collection Performance of Rail Pantograph-Catenary Considering Long Suspension Bridges” in IEEE Transactions on Instrumentation and Measurement. He is a member of the China Power Supply Society and serves as a reviewer for several leading journals, including IEEE Transactions on Instrumentation and Measurement, IEEE Transactions on Reliability, and Journal of Vibration and Control.