DMS Colloquium: Jingyi Zheng

Speaker: Dr. Jingyi Zheng (Auburn University)

Title: Statistical Learning for Spatial-temporal Data in Biomedical Applications

Abstract: Biomedical data science has been an emerging field in recent years. It focuses on the development of novel methodologies to analyze large-scale biomedical datasets in order to advance biomedical science discovery. Spatial-temporal data is one of the most commonly encountered data types not only in biomedical fields but also in a variety of disciplines such as agriculture, computer vision, geosciences, and hydroclimatology. In this talk, I will present two types of methods developed for analyzing the spatial-temporal data: data-driven time frequency analysis and a manifold-based framework for analyzing positive semi-definite matrices. The applicability, efficiency, and interpretability of each method will be demonstrated by extensive simulations and real data applications.