报 告 人：邱培华 教授(佛罗里达大学)
报告题目：Mathematics, Statistics, and Data Science: My personal Experience and Perspectives
报告时间：2018年6月11日（周一）上午9：30
报告地点：静远楼1506学术报告厅
报告人简介：
邱培华教授于1996年获得威斯康星大学麦迪逊分校统计系的博士学位,在1996 - 1998年期间担任俄亥俄州立大学生物统计学中心的高级研究咨询统计员,之后在明尼苏达大学统计学院担任助理教授(1998-2002),副教授(2002-2007)和正教授(2007-2013).邱培华教授是美国统计协会成员、数学统计研究所成员、国际统计研究所成员、美国质量协会的高级成员以及国际中国统计协会的终身成员。他曾先后担任Journal of the American Statistical Association (2006-2012), Biometrics (2011-2012), Technometrics (2007-2012)和Statistical Papers (2011-2012) 的Associate Editor,以及Multimedia Tools and Applications和Quality and Reliability Engineering International的Guest Co-Editor。2013年成为Technometrics的Editor-elect并在2014年到2016年成为Editor。邱培华教授自2013年7月1日起开始在佛罗里达大学工作,是佛罗里达大学生物统计学系的Founding Chair。
邱培华教授在Jump Regression Analysis,图像处理,统计过程控制,生存分析和疾病筛查与监测等领域做出了很大贡献.迄今为止,他发表了100多篇研究论文,其中许多发表在顶尖期刊上,包括Technometrics, Journal of the American Statistical Association, Annals of Statistics, Annals of Applied Statistics, Journal of the Royal Statistical Society (B), Biometrika, Biometrics, IEEE Transactions on Pattern Analysis and Machine Intelligence 和 IIE Transactions。邱培华教授的研究专著Image Processing and Jump Regression Analysis (2005,Wiley) 弥补了统计学中的Jump Regression Analysis与计算机科学图像处理之间的差距,在2007年获得了首届Ziegel奖.邱培华教授的第二本专著Introduction to Statistical Process Control于2014年由Chapman＆Hall / CRC出版。
报告摘要：
In recent years, big data, data science, and data informatics are popular words. General people do not know much about their difference and their connection with statistics, mathematics and computer science. The speaker had mathematics as his original major, then studied and researched statistics for more than two decades, and much of his research focused on images and other computer science topics. In this talk, the speaker will share with the audience about i) his study and career experience in mathematics, statistics and computer science, ii) his major research topics, and iii) his personal perspectives about big data and data science. He will also briefly introduce his department and graduate programs during the talk, in the case undergraduate and graduate students are interested in joining his department in the future. The presentation will be prepared for a general audience who do not need to know much of statistics. But, statistical researchers should also find it helpful.