Statistical and Computational Theory and Methodology for Big Data Analysis (14w5086)


(University of Connecticut)

(University of Toronto)

(Texas A&M University)

Chuanhai Liu (Purdue University)


The Banff International Research Station will host the "Statistical and Computational Theory and Methodology for Big Data Analysis" workshop from February 9th to February 14th, 2014.

The integration of computer technology into science and daily life has enabled the collection of
big data sets. Today we live in an era of observations: data come from many disparate sources,
such as sensor networks, scientific instruments, financial transactions, internet communications,
and scientific simulations. These new sources of data and their increasing complexity
contribute to an explosion of information.
Opportunities abound for learning from massive-scale data sets, which can provide researchers
and decision makers with information of enhanced range, quality, and depth.
The goal of this workshop is to bring together scientists and statisticians to stimulate and exchange
innovative ideas for theoretical and methodological advances in analyzing and modeling big data.

The Banff International Research Station for Mathematical Innovation and Discovery (BIRS) is a collaborative Canada-US-Mexico venture that provides an environment for creative interaction as well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disciplines and with industry. The research station is located at The Banff Center in Alberta and is supported by Canada's Natural Science and Engineering Research Council (NSERC), the U.S. National Science Foundation (NSF), Alberta's Advanced Education and Technology, and Mexico's Consejo Nacional de Ciencia y Tecnología (CONACYT).