体育投注现金网_沙巴体育-娱乐场*官网@

图片

搜索
你想要找的

热门搜索

建党100周年70周年校庆卓越育人学术育人不言之教幸福之花

9月23日 袁明:Information Based Complexity for High Dimensional Statistical Models(69周年校庆系列学术报告)
2021-03-29 22:18:24
活动主题:Information Based Complexity for High Dimensional Statistical Models
主讲人:袁明
举行地点:线上 Zoom会议 ID:683 4896 5096

 

报告人简介:

    Ming Yuan is Professor of Statistics at Columbia University. He was previously Senior Investigator in Virology at Morgridge Institute for Research and Professor of Statistics at University of Wisconsin at Madison, and prior to that Coca-Cola Junior Professor of Industrial and Systems Engineering at Georgia Institute of Technology. His research and teaching interests lie broadly in statistics and its interface with other quantitative and computational fields such as optimization, machine learning, computational biology and financial engineering. He has over 100 scientific publications in applied mathematics, computer science, electrical engineering, financial econometrics, medical informations, optimization, and statistics among others. He is currently serving as the program secretary of the Institute for Mathematical Statistics (IMS), and a member of the advisory board for the Quality, Statistics and Reliability (QSR) section of the Institute for Operations Research and the Management Sciences (INFORMS). He is also a co-Editor of The Annals of Statistics and has been serving on numerous editorial boards. He was named a Medallion Lecturer of IMS in 2018, and a recipient of the John van Ryzin Award (2004; International Biometrics Society), CAREER Award (2009; US National Science Foundation), the Guy Medal in Bronze (2014; Royal Statistical Society), and the Leo Breiman Junior Researcher Award (2017; the Statistical Learning and Data Mining section of the American Statistical Association).