My current cv is available for download in PDF format.

A list of my publications can be found here: Publication List

My Google Scholar profile: Google Scholar Profile

• Ph.D. in Statistics (2004) from the Department of Statistics at Harvard University.
  
  Ph.D. thesis: Statistical Techniques for Examining Gene Regulation
  
  Winner of the Leonard J. Savage Award for best thesis in Application Methodology
  from the International Society for Bayesian Analysis
  
  
• A.M. in Statistics (2001) from the Department of Statistics at Harvard University.
• M.Sc in Statistics (1999) from the Department of Mathematics and Statistics at McGill University.
  M.Sc. thesis: The Laguerre-Samuelson Inequality
• B.Sc in Mathematics and Biology (1997) from the Departments of Mathematics and Statistics and Biology at McGill University.

I enjoy developing statistical methodology for a wide variety of application areas. Some of my current interests are:

1. Genetics and Molecular Biology

Developing sophisticated statistical models for the evolution of genomic sequences. Areas of application include the response of HIV under various therapies as well as evolution during cancer progression. Developing models for combining heterogeneous data sources to refine predictions about co-regulated genes and regulatory networks in cells.

2. Statistics in Sports

Developing novel statistical models for the comparison of baseball players in terms of on-field performance. Evaluation of fielding ability as well as prediction of future hitting and pitching performance. Quantifying player performance in hockey.

3. Bayesian Nonparametrics

Extensions of Dirichlet processes for grouped and ordered data. Alternative prior processes for non-parametric clustering. Tree-based approaches for high-dimensional settings.

4. Economics and Marketing

Estimating income volatility while allowing for heterogeneity over time and between individuals in the population. Exploring the relationship between income volatility and risk aversion. Modeling career choice as a function of risk aversion. Models for missing data in marketing research.

COGRIM: Bayesian variable selection model for regulatory network inference through the integration of gene expression data, ChIP binding data and sequence motif data.

PHYLOCLUS: Suite of perl programs for clustering co-regulated genes based on phylogenetically discovered transcription factor binding motifs.

MOTIF CLUSTERING: Perl programs and supplemental material for clustering transcription factor binding motif matrices based on a hierarchical Bayesian model.

2013/02/13: Article about my hockey research with Bobby Gramacy and Matt Taddy at Chicago Booth School of Business which was also linked by the Wall Street Journal

2009/10/26: Another interview about my fielding research on Scienceline

2009/01/26: More coverage of my income volatility research with Stephen Shore on the Marginal Revolution Blog

2008/07/14: Another mention of our fielding research in Slate

2008/06/25: Coverage of my income volatility research with Stephen Shore on the Freakonomics Blog

2008/02/21: The NY Post and Jeter himself responds to our fielding research! NY Post Jeter Response

2008/02/10: Our NY Times article about Roger Clemens: NY Times Link PDF file