Xilin Luo

Xilin Luo is a researcher in Management Science and Engineering working at the intersection of energy forecasting, time series analysis, machine learning, grey system theory, and forecasting model security. His research focuses on data-driven forecasting, model robustness assessment, and risk management in complex energy environments, with the aim of supporting energy system operation, forecasting-based decision-making, and security management.

Xilin holds a PhD in Management Science and Engineering from Sichuan University, with interdisciplinary training in systems science and industrial engineering. He was a visiting scholar at the Department of Business Administration, National and Kapodistrian University of Athens, where he conducted research on time series forecasting methods and their applications in energy systems. His recent work further examines the performance of forecasting models under data perturbations, abnormal fluctuations, and adversarial settings, and explores security-oriented evaluation frameworks and threshold management mechanisms for energy forecasting.

Xilin has published more than ten papers in leading international and Chinese academic journals, including Energy, Chaos, Solitons & Fractals, Applied Soft Computing, ISA Transactions, and Chinese Journal of Management Science. His research covers energy consumption forecasting, grey forecasting models, machine learning-based prediction, and forecasting model security assessment. He also serves as an anonymous reviewer for several international journals, including journals from the Nature portfolio, Chaos, Solitons & Fractals, and ISA Transactions. In addition, he has participated in three national-level research projects related to data-driven forecasting methods and their applications in complex systems, and has received several academic honours, including the National Scholarship for Graduate Students and the China Scholarship Council award.