Surya Tokdar Awarded Leonard J. Savage Award

05-09-2007

Surya Tokdar

Congratulations to Surya Tokdar, August 2006 Ph.D. Statistics graduate, on being awarded the Leonard J. Savage Award for best dissertation in Theory and Methods. He was selected among four finalists who presented their work at the Leonard J. Savage Awards Topic Contributed Papers session held during the 2007 Joint Statistical Meetings. His dissertation was titled "Exploring Dirichlet Mixture and Logistic Gaussian Process Priors in Density Estimation, Regression and Sufficient Dimension Reduction." Professor Jayanta K. Ghosh was his Ph.D. advisor.

The Leonard J. Savage Award is awarded each year to two outstanding doctoral dissertations in Bayesian econometrics and statistics. One award is given to the best dissertation in Application Methodology and the other is given to the best dissertation in Theory and Methods. The Theory and Methods award is granted for a dissertation that makes important original contributions to the foundations, theoretical developments, and/or general methodology of Bayesian analysis.

The award is sponsored by the International Society of Bayesian Analysis, the American Statistical Association Section on Bayesian Statistical Science (SBSS), and the NBER/NSF Seminars on Bayesian Inference in Econometrics and Statistics.

Surya Tokdar is the Morris H. DeGroot Visiting Assistant Professor in the Department of Statistics at Carnegie Mellon University.

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