Dr. Hongxiang Zhang is an Assistant Professor. He began his studies at the School of Transportation and Logistics, Southwest Jiaotong University, in 2014, where he successively completed his bachelor’s, master’s, and doctoral degrees, receiving his Ph.D. in Engineering in December 2025. During his doctoral studies, he was sponsored by the China Scholarship Council (CSC) to conduct joint Ph.D. research at Eindhoven University of Technology (TU/e), the Netherlands.

His research focuses on the simulation and data-driven optimization of rail transportation operations. In recent years, he has been dedicated to the deep integration of deep reinforcement learning, graph neural networks, and simulation technologies, achieving a series of innovative results in the simulation and optimization of railway marshalling yard operations, the simulation and optimization of high-speed railway station operations, train headway compression, and passenger flow situation inference for urban rail transit networks. He has published more than 20 academic papers, including six first-author papers in SCI Q1 journals such as Transportation Research Part C, International Journal of Rail Transportation, and Simulation Modelling Practice and Theory. His work has been cited over 300 times on Google Scholar, and he holds two granted national invention patents.

He is the Principal Investigator of a project funded by the Young Scientists Fund (Class C) of the National Natural Science Foundation of China (NSFC), and has participated in three projects under the National Key Research and Development Program of China and two NSFC projects. In 2026, he was selected for the Young Elite Scientist Sponsorship Program (YESS) of the China Association for Science and Technology (CAST).

He is a member of the China Simulation Federation (CSF) and has long served as a reviewer for leading international journals, including Transportation Research Part C and IEEE Transactions on Intelligent Transportation Systems. His academic honors include Third Place in the 2020 INFORMS Railway Applications Section (RAS) Problem Solving Competition, First Prize in the 2022 CSF Complex Systems Simulation and Modeling Competition, and the 2026 CSF High-Quality Doctoral Dissertation Award.