Workshop on Statistical Research in the era of Big Data

It is both the best and worst time for statistics and statisticians. Perhaps uniquely, the discipline of statistics experiences a thorough renewal every few years. We devote research enthusiasm to classical theory, biostatistics, industrial statistics, data mining, genomics, and large-p-small-n problems. At the moment, advances in information technology lead us to big data and deep learning. The combination of the availability of large amounts of data, often in new and complex forms, and the advances in computational power makes for exciting times for statisticians. Equally truthfully, the big data may put some at serious risk of becoming obsolete before ever earned the right to be called statisticians! We call for a workshop not to show-off new and exciting research achievements on big data. Rather, we wish to exchange ideas on how to avoid being swept away by the wave of the big data. Whether you intend to stick to the current research problems, completely reinvent yourself, or bring your current skills to claim a territory of big data, we wish to hear from you.

Confirmed Speakers

Jiahua Chen (UBC)

Xin Gao (York University)

Xuewen Lu (University of Calgary)    

Xiaoping Shi (Thompson Rivers University) 

Lan Liu (University of Minnesota at Twin Cites)

Minge Xie (Rutgers University)

Mark Wolters (Fudan University)

Lixing Zhu (Hong Kong Baptist University and Beijing Normal University) 

Xuekui Zhang, University of Victoria

Click here for Speaker Abstracts

Click here for the Program Schedule