I received my Ph.D. in statistics from the University of Chicago in 1980. My early work was in geometrical methods, in the mid-1980s I turned to Bayesian inference, and then in 2000 I began studying statistical methods in neuroscience. I am actively involved not only in the Department of Statistics (where I served as head for nine years), but also the Machine Learning Department and the Center for the Neural Basis of Cognition (where I am currently Interim Co-Director).
I am broadly interested in statistical methods in neuroscience, but most of my publications have concerned statistical analysis of spike train data, i.e., the output of single-electrode and multiple-electrode neurophysiological experiments. For an overview of my research in this area, see http://www.stat.cmu.edu/~kass/contrib.html. I am also supervising several students working on MEG, fMRI and diffusion imaging, and I hope to learn about statistical issues in applying other neuroscience technologies.