Peter Radchenko’s research focusses on developing and analysing novel methodology for dealing with massive and complex modern data. Fields ranging from finance, marketing and economics to image analysis, signal processing, data compression and computational biology nowadays share the common feature of trying to extract information from vast noisy data sets. The age of Big Data has created an abundance of interesting problems, posing new challenges, not present in conventional data analysis. Such large scale problems fall under the general framework of High Dimensional Statistics and Statistical Machine Learning, which are the primary areas of Peter Radchenko’s research. His main focus has been on the problems in high-dimensional regression, convex clustering and functional data analysis.
