报告题目：生物医学时空大数据的统计建模（Statistical Learning for Spatial-temporal Data in Biomedical Applications）
报告人：Jingyi Zheng,Department of Mathematics and Statistics，Auburn University，USA
主持人：李娜(统计与数学学院副院长 二级教授)
报告地点：舜耕校区4号楼315会议室
报告时间：2023年6月30日（周五）15：00-17：00
主办单位：山东财经大学统计与数学学院
摘要:
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. The applicability, efficiency, and interpretability of each method will be demonstrated by extensive simulations and real data applications.
报告人简介：
郑婧怡，现任奥本大学数学与统计学院副教授，2019年获得加州大学戴维斯分校统计博士学位。研究集中于数据科学、统计建模和机器学习，包括高维数据分析、时空数据建模、信号和图像处理以及深度学习等研究方向。其研究得到了美国国家科学基金会（NSF）和美国国家卫生研究院（NIH）的多个基金项目资助。