Date & Time: July 10, 2018 15：30 p.m. - 17：00 p.m.
Venue: SEM 104 Auditorium
Abstract：
The explosive growth of Big Data brings significant challenges and potentials to a wide range of fields, from genomics to personalized medicine to information technology. It also creates tremendous opportunities for statistics. The emergence of data science promises to revolutionize industries from business to health care to government, and to change how we work, live and communicate. In this non-technical talk, I will discuss a few interesting problems to illustrate the potential benefits of Big Data and the demand for statistics in the age of Big Data. The emergence of data science requires substantially expansion of statistics programs in leading universities.
Speaker Biography：
Tony Cai is Vice Dean of the Wharton school, Dorothy Silberberg Professor of Statistics at Wharton School, professor of Applied Math & Computational Science Graduate Group, and senior scholar at the Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania. In 2006, Professor Cai was elected as a fellow of the Institute of Mathematical Statistics. In 2008, he was given the COPSS Presidents’ Award — an award regarded as “the Nobel Prize” of Statistics — by the Committee of Presidents of Statistical Societies. In 2017, he was elected to the presidency of International Chinese Statistical Association (ICSA). He served as the editor of Annals of Statistics and has served on the editorial boards of many academic journals.
Professor Cai earned his PhD in Statistics at Cornell University, where he studied under Lawrence. D. Brown, a member of United States National Academy of Sciences. Professor Cai has focused his research on Big Data Analytics, including the areas of statistical inference on high-dimensional data, statistical machine learning, large-scale multiple testing, functional data analysis, statistical decision theory, nonparametric function estimation, as well as applications to genomics, and financial engineering.
