Program Head, Cognitive Science BS and Applied Cognition and Neuroscience MS
Mathematical analysis and design of statistical machine learning algorithms with applications to modeling problems in neural, behavioral, and social sciences
Dr. Richard Golden is a leading researcher in the field of the mathematical analysis and design of statistical machine learning algorithms with applications to modeling problems in neural, behavioral, and social sciences. His research includes asymptotic behavior of stochastic adaptive nonlinear learning machines, statistical inference in the simultaneous presence of missing data and model misspecification, specification tests for detecting presence of model misspecification, and model selection in the presence of uncertainty. Dr. Golden is an invited consultant to the Panel on Statistics and Analytics for VHA datasets. And, for over a decade, Dr. Golden served on the Editorial Boards of the Journal of Mathematical Psychology and Neural Networks. Dr. Golden earned his bachelor’s degree at the University of California at San Diego, and his master’s and doctoral degrees at Brown University.
Mathematical Methods for Neural Network Analysis and Design. Golden, R. M. (1996). MIT Press, Cambridge, MA. [419 pages].
Recent Peer-Refereed Book Chapters and Journal Articles
Golden, R. M., Henley, S.S., White, H., Kashner, T. M. (2013). New Directions in Information Matrix Testing: Eigenspectrum Tests in Norman Swanson and Xiohang Chen (Eds.) Causality, Prediction, and Specification Analysis: Recent Advances and Future Directions Essays in Honour of Halbert L. White, Jr. New York: Springer, pp. 145-178.
Kashner, T. M., Henley, S. S., Golden, R. M., Bryne, J. M. Sheri, A., Cannon, G. W., Chang, B. K., Holland, G. J., Aron, D. C., Wicker, A., and White, H. (2010). Studying the Effects of ACGME duty hours limits on resident satisfaction: Results from VA Learners’ Perception Survey. Academic Medicine, 85, 1130-1139.