讲座题目：Deep Learning and Applications in Survival Analysis

主讲人：洪益力教授 弗吉尼亚理工大学

讲座时间：2019年6月10日（星期一）8:30-16:00

2019年6月11日（星期二）8:30-11:30

2019年6月12日（星期三）8:30-11:30

讲座地点：综合楼601

主讲人简介：Yili Hong received a BS in statistics in 2004 from University of Science and Technology of China. He received his MS in statistics in 2005 and PhD in statistics in 2009 from Iowa State University. He is currently an Associate Professor in the Department of Statistics at Virginia Tech. His research mainly focuses on statistical reliability. Areas include lifetime data analysis, field failure prediction, accelerated life test planning and analysis, accelerated degradation test planning and data analysis, system health monitoring, and applications in engineering, chemistry and material sciences. His research has been published in top journals such as Technometrics, JQT, Annals of Applied Statistics, JASA, IEEE Transactions on Reliability, and Quality Engineering. He is one of the recipients of the 2011 DuPont Young Professor Award. He is an associate editor for Technometrics and JQT. He is a co-guest editor for a special issue on big data in reliability for JQT. He is an elected member of International Statistical Institute.  

讲座摘要：Survival data, or more generally referred to as time to event data, are very common in many areas. In some applications, the objective is to predict the time to event. Deep learning techniques have been successfully applied to many prediction problems. This course explores the potential applications of deep learning in time to event predictions. The first part covers essentials in survival analysis and prediction problems in survival analysis. The second part covers basics in deep learning, convolutional neural networks, and recurrent neural networks and their applications in time to event prediction.