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                The Whiting School of Engineering
                   The Johns Hopkins University

                  INAUGURAL PROFESSORIAL LECTURE 

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Carey E. Priebe                             November 29, 2001
Department of Mathematical Sciences         Arellano Theatre (note change) 
The Johns Hopkins University                Seminar: 3:00 p.m.(note change)
                                            Reception: 4:00 pm

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         INVESTIGATING THE STRUCTURE OF HIGH DIMENSIONAL 
               PATTERN RECOGNITION PROBLEMS 


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                               ABSTRACT

Statistical pattern recognition (classification, clustering, etc.) in 
high dimensions is notoriously difficult -- the "curse of dimensionality" 
implies that 'enough' data will never be available.  Nevertheless, high 
dimensional pattern recognition applications such as hyperspectral target 
recognition and gene expression monitoring require methodologies for 
uncovering structure, generating hypotheses, and making decisions.  This 
talk will discuss some of the challenges presented by high dimensional 
pattern recognition problems, and will introduce a "statistical data 
mining" methodology for investigating the structure of these problems.
Applications from artificial olfactory analysis (the Tufts University 
"artificial nose") and gene expression monitoring by DNA microarrays
will be used to frame the discussion.