Craig Agate is a Chief Scientist and Fusion and Tracking Group Lead at Toyon Research Corporation. He received the B.S. and M.S. degrees in electrical engineering from California State University in Northridge, California and a Ph.D. in electrical engineering from the University of California in Santa Barbara where his doctoral thesis dealt with state and parameter estimation using density function approximation. In particular, he analyzed the small-sample and large-sample properties of a nonlinear parameter estimation algorithm that minimizes the Kullback-Leibler distance between the probability density function (PDF) of an unknown parameter and a mixture density. His interests lie in tracking targets using passive RF, track identity management algorithms, track-to-track fusion algorithms, and general problems in information fusion.