I am a computational biologist, specializing in population genetics and genome analysis.

Unlike most computational biologists, who start off in computer science or statistics, I started my career as a 'wet lab' biologist and gradually trained in statistical and computational techniques as I perceived the need arise.  After my post-doc, I decided to spend a few years solidifying my knowledge in fundamental analytical techniques (see my CV for more details). 

Like all scientists, I'm interested in generating new knowledge in my realm of interest -- biology.  My approach to this is to use computational and statistical techniques to analyze the rapidly increasing amounts of raw descriptive data generated by wet lab biologists.

I'm also very interested in using biological knowledge to solve problems (health-, energy-, waste-, and food-related), as an engineer.

I'm currently working  with Christine Queitsch and Su-In Lee to develop a method that identifies functional regions of the genome by integrating data sets that describe different aspects of the genome (e.g., evolutionary conservation, epigenetic markers, expression levels, linkage maps).

Here's my CV, a list of my publications, and my graduate thesis, The Role of Balancing Selection in Maintenance of Natural Genetic Variation.

Here's a link to some math notes I've written up on some useful math and statistical analysis techniques.  I included a draft of my budding data analysis (for dummies) manifesto, "How to Analyze Lots of Data", which I have since realized was my attempt to reinvent machine learning.