Jingsong Yuan

Jingsong Yuan is a Lecturer specializing in Statistics. His research focuses on higher-order spectral analysis of time series and random fields, asymptotic theory of spectral estimation, and applications in signal and image processing. He is affiliated with the Statistics and its Applications research group and contributes to the Digital Futures research beacon.

• Research Interests: Time series analysis, copula models, statistical signal processing
• Projects: Lead investigator in the Statistical Advisory Unit (SAU), focusing on inferential statistics and nonlinear models.

His work bridges theoretical statistics with practical applications, particularly in energy price forecasting via deep learning (e.g., DeepTVAR model) and medical imaging analysis (e.g., dental panoramic radiography studies). He is actively supervising PhD students in time series analysis and forecasting.

Collaborations span international researchers, with recent work emphasizing deep learning integration into traditional statistical models like VAR and ARMA frameworks.