Statistics Seminar Speaker: Steve Marron, 04/27/2016

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Wednesday Apr 27 2016

Statistics Seminar Speaker: Steve Marron, 04/27/2016

4:15pm @ G01 Biotechnology

The Statistics Seminar Speaker for Wednesday, April 27, 2016, is Steve Marron, Amos Hawley Professor of Statistics and Operations Research at the University of North Carolina. 

J. S. Marron is the Amos Hawley Distinguished Professor of Statistics and Operations Research, at the University of North Carolina, Chapel Hill.  He received the B. S. degree from the University of California at Davis, and the Ph. D. from the University of California at Los Angeles.  Marron has held the positions of Assistant, Associate and Full Professor with the University of North Carolina, Chapel Hill, and is also Professor of Biostatistics and Adjunct Professor of Computer Science and Member of the Lineberger Comprehensive Cancer Center. 

He was a founding Associate Director of the Statistical and Applied Mathematical Sciences Institte (SAMSI).  He has also served as Mary Upson Distinguished Professor of Operations Research at Cornell University, and held 13 other visiting positions in four countries.  Marron is an elected Fellow of the American Statistical Institute and the Institute for Mathematical Statistics, and an elected Member of the International Statistical Institute.  Marron has served as Associate Editor for the Annals of Statistics, the Journal of the American Statistical Association, the Journal of Nonparametric Statistics, Computational Statistics and Test. 

He is currently Associate Editor of the Electronic Journal of Statistics.  Marron has presented the Theory and Methods Invited Paper for the Journal of the American Statistical Association, been the Institute of Mathematical Statistics Medallion Lecturer, and presented the S. N. Roy Memorial Lecture at the University of Calcutta.  He has delivered the Bradley Lecture at the University of Georgia, and the Information Science and Technology Center Distinguished Lecture at Colorado State University.

Title: Object Oriented Data Analysis 

Abstract: Object Oriented Data Analysis is the statistical analysis of populations of complex objects. In the special case of Functional Data Analysis, these data objects are curves, where standard Euclidean approaches, such as principal components analysis, have been very successful. Challenges in modern medical image analysis motivate the statistical analysis of populations of more complex data objects which are elements of mildly non-Euclidean spaces, such as Lie Groups and Symmetric Spaces, or of strongly non-Euclidean spaces, such as spaces of tree-structured data objects. These new contexts for Object Oriented Data Analysis create several potentially large new interfaces between mathematics and statistics. The notion of Object Oriented Data Analysis also impacts data analysis, through providing a language for discussion of the many choices needed in many modern complex data analyses. 

Note: Refreshments will be served before the seminar at 3:45 pm in 1181 Comstock Hall. 

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