Assistant Professor Department of Statistics and Actuarial Science
University of Waterloo
Waterloo, Ontario
CANADA N2L 3G1
(519) 888-4567, ext. 37317
Fax: (519) 746-1875
Email:
Office: M3 3124
Professor Chenouri's research interests concern many areas of statistics, including multivariate nonparametric robust methods, data depth, robust statistical machine learning and data mining, computational statistics, biostatistics, asymptotics, and the foundations of statistics.
Multivariate statistical methods have regularly been applied to problems arising in many branches of science such as the physical, social, and medical sciences. Classical multivariate analysis relies heavily on the assumption of normality or ellipticity, which is often difficult to justify in practice. One of Professor Chenouri's current interests concerns developing nonparametric robust methods for multivariate data (both completely observed and censored) using the concept of data depth.
Professor Chenouri has also been working on developing statistical and computational methods to analyze high-dimensional data such as images, curves, and genetic microarrays. He is particularly interested in methods that are robust and distribution free.
Professor Chenouri received his PhD in 2005 from the University of Waterloo. From September 2004 to July 2005 he was an assistant professor in the School of Mathematics and Statistics, Carleton University. From 1993 to 2001 he consulted for industry and medical research. He was also involved in projects at the Intelligent System Section of the Institute of Theoretical Physics and Mathematics (IPM) in Iran, the Statistical Research Center of Iran, and the Amarpardazan Company in Tehran. He held an administrative job (1997--99) at the Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran. He has also been a lecturer in statistics and mathematics at Shahid Beheshti University and several other institutions in Iran.