Conference proposal: From Industrial Statistics to Data Science

Regents Of The University Of Michigan - Ann Arbor, Ann Arbor MI

Investigators

Abstract

The conference "From Industrial Statistics to Data Science" will be held October 1-3, 2015, in Ann Arbor, Michigan, on the University of Michigan campus. The theme of the conference is a path toward addressing the next generation of critical challenges in science and industry to which statisticians can contribute, building upon the strong legacy of industrial statistics that has resulted from the contributions of many researchers in academia and in industry. The conference will feature approximately 20 invited speakers, from both academia and industry, many of whom have made fundamental contributions to industrial statistics, data science, and allied areas of statistical methodology, and a student poster session. This award will support registration and travel to the conference for students, postdoctoral fellows, and junior researchers. Recent crystallization of interest around the term "Data Science" provides a framework for thinking about ways to effectively build on the contributions of industrial statisticians and leverage the well developed classical frameworks in modern applications. Industrial statistics with its focus on reliability and design of experiments has traditionally been an area of statistics with strong connections to industry. In the era of data science, many of the traditional areas such as design of experiments are as relevant as ever, but new connections need to be made to bring these ideas into the context of big data. To address this need and help build relevant connections, the conference program will include sessions on industrial statistics, data science, and new methodologies for addressing challenging problems in natural science, social science, and engineering, with a view toward how research in these areas contributes to critical national and global priorities. More information about the conference can be found at https://sites.lsa.umich.edu/vn65.