Ms. Zhongwen Wu | Artificial Neural Networks | Research Excellence Award

Wu Zhongwen is a researcher in complex networks and systems science with a strong background in applied mathematics and neural system modeling. His work focuses on the stability, synchronization, and dynamical behavior of fractional-order and quaternion-valued neural networks, particularly under time-varying delays and switching mechanisms. He has authored multiple first-author SCI journal articles in leading international venues, with research contributions spanning equilibrium coexistence, asymptotic stability, and finite-time synchronization criteria. Wu has also served as a principal investigator for a competitive provincial youth research grant, reflecting recognition of his independent research capability. Trained through rigorous graduate and doctoral studies in applied mathematics, he combines solid theoretical analysis with advanced tools from nonlinear dynamics, fractional calculus, and complex network theory. His research aims to deepen the mathematical understanding of neural systems and provide robust analytical frameworks applicable to intelligent systems, control theory, and interdisciplinary networked dynamics.