Peter Radchenko

Professor of Statistics at the University of Sydney Business School.

I am interested in developing new methodology for dealing with massive and complex modern data, particularly in the area of high-dimensional regression. A more recent line of my research takes advantage of the advances in mixed integer optimization and modern optimization techniques to analyse key discrete problems arising in statistics. I have also worked on the problems of large-scale cluster analysis, large-scale estimation and inference, correlation screening, forecast reconciliation, and functional data analysis.

Prior to joining the University of Sydney, I held academic positions in the Marshall School of Business at the University of Southern California and in the Statistics Department at the University of Chicago. I have a PhD in Statistics from Yale University (advisor: David Pollard), and an undergraduate degree in Mathematics from the Lomonosov Moscow State University.