Professor, Statistics Carnegie Mellon University Phone: (412) 268-2725 Fax: (412) 268-7828 Email: bill@cmu.edu

Ph.D., Yale University

Research Interests

In the last six years I have become keenly interested in the statistical problems associated with fMRI. A typical fMRI experiment run by a cognitive psychologist produces as much as 1 gigabyte of data per hour. The computational challenges are obvious.

The statistical challenges in the analysis of fMRI data are difficult and manifold. They all revolve around our understanding the nature of the noise and its effect on successfully detecting regions of activation. There are two general approaches to dealing with the noise in fMRI experiments. The first is to try to remove the source of the noise; we pursue this approach aggressively. The second is to model the noise through statistical methods; we also pursue this approach aggressively. We believe that both approaches are absolutely necessary.

Recent Publications

• Lazar NA, Eddy WF, Genovese CR, Welling J: Statistical issues in fMRI for brain imaging. To appear in International Statistical Review.
• Eddy WF, Young TK: Optimizing MR resampling. To appear Handbook of Medical Image Processing, Isaac Beckman, Ed., Academic Press, San Diego, 2000.
• Goddard NH, Hood G, Cohen JD, Nystrom LE, Eddy WF, Genovese CR, Noll DC: Functional magnetic resonance imaging dataset analysis. Industrial Strength Parallel Computing (A.E. Koniges, Ed.) , Morgan Kaufmann Publishers, 431-451, 2000.
• Eddy WF, Fitzgerald M, Genovese C, Lazar N, Mockus A, Welling J: The challenge of functional magnetic resonance imaging. Journal of Computational and Graphical Statistics, 8, 3, 545-558, 1999.