报告题目：Predictive Models, Big Data and Applications
报告人：史建清教授（英国纽卡斯尔大学）
报告时间：2019年4月2日(星期二)14:00-15:00
报告地点：尚贤楼706
主持人：曹春正教授
报告内容简介：
Using data collected from low-cost wearable sensors on precision medicine becomes a popular and important research for ageing. Statistical analysis is however very challenging due to their complex structure, large noise ratio, very large scale (usually in size of terabytes) and also the big variation among subjects.
In this talk, I will discuss how to use some modern statistical models to develop predictive, classification or clustering tools for precision monitoring and timely diagnoses of neurological conditions and disorders, enabling real-time evidence-based decision making; focusing examples of upper limb rehabilitation after stroke and age related neurodegenerative diseases (dementia and Parkinson’s disease), both involving neurological disorders.
报告人简介：
史建清，英国纽卡斯尔大学数学与统计学院教授、大数据与云计算博士生研究中心副主任，英国图灵研究所研究员，我校非全时教授，统计学国际知名学者，主要研究方向包括函数型数据分析、缺失数据和模型不确定性分析、医学统计以及大规模系统监控等，历任Journal of the Royal Statistical Society (Series C)等多家统计学顶尖杂志编委。在国际权威出版社Chapman & Hall出版专著《Gaussian Process Regression Analysis for Functional Data》，关于函数型数据分析等系列研究成果发表在Journal of the American Statistical Association、Journal of the Royal Statistical Society Series B、Biometrika、Biometrics等统计学顶尖杂志。合作论文荣获非参数统计杂志和美国统计协会非参数统计主题最佳论文奖。
数学与统计学院
2019年4月1日
