Dianne Cook

Dianne Cook is a leading figure in the fields of data visualization, exploratory data analysis, multivariate methods, data mining, and statistical computing.

Her extensive research includes work on visualizing data in virtual environments and contributing to the development of various software tools like xgobi, ggobi, cranvas, and multiple R packages.

Cook's methodological contributions encompass tours, projection pursuit, manual controls for tours, pipelines for interactive graphics, a grammar of graphics for biological data, and visualizing boundaries in high-dimensional classifiers.

Her current focus lies in bridging the gap between statistical inference and exploratory graphics, with ongoing experiments using Amazon's Mechanical Turk and eye-tracking equipment.

Throughout her career, Cook has applied her expertise to a diverse range of applications including backhoes, drug studies, climate change, gene expression analysis, butterfly populations in Yellowstone, and a variety of other fields.

She holds a Doctor of Philosophy (PhD) in Statistics from Rutgers University and a Bachelor of Science with a Diploma of Education in Mathematics and Statistics from the University of New England (AU).

Previously, she served as a Professor of Business Analytics at Monash University.