时 间：2026年10月26日（周一）10：00
地 点：中北理科大楼A1514室
报告人：Jian Qing Shi 北师香港浸会大学 讲座教授
邀请人：於州 华东师范大学统计学院
摘 要：
Motivated by distinct walking patterns in real-world free-living gait data, this talk will discuss an innovative curve-based sampling scheme for the analysis of functional data characterized by a mixture of covariance structures. Traditional approaches often fail to adequately capture inherent complexities arising from heterogeneous covariance patterns across distinct subsets of the data. We introduce a unified Bayesian framework that integrates a nonlinear regression function with a continuous-time hidden Markov model, enabling the identification and utilization of varying covariance structures. One of the key contributions is the development of a computationally efficient curve-based sampling scheme for hidden state estimation, addressing the sampling complexities associated with high-dimensional, conditionally dependent data. This talk details the Bayesian inference procedure, examines the asymptotic properties to ensure the structural consistency of the model, and demonstrates its effectiveness through simulated and real-world examples.
报告人简介：
Dr Jian Qing Shi is a Fellow of the Royal Statistical Society and Chief Scientist of the National Key R&D Program of China. He serves as Chair Professor of Statistics and Data Science and Executive Dean of the Graduate School at Beijing Normal-Hong Kong Baptist University (BNBU). Before joining BNBU in 2026, He was Professor of Statistics and Director of the Center for Biostatistics at Southern University of Science and Technology, China. He also served as Reader in the School of Mathematics, Statistics & Physics and Assistant Director of the Cloud Computing for Big Data CDT at Newcastle University, and as a Turing Fellow at the Alan Turing Institute UK. His research interests include the analysis of big health data for aging, functional data analysis, Bayesian nonparametric analysis for big data, missing data, meta-analysis, with applications in medicine and system control. Dr Shi is the principal investigator for several significant research projects in both China and UK, including the National Key R&D Program of China (PI, 11.1 million RMB). He has also been a visiting research fellow in Newton Institute at Cambridge in the UK and SAMSI in the USA. Along with his team, he has produced many influential and original research contributions, earning recognition in the statistics community, including two recent international best paper awards.