I am a postdoctoral fellow in Rafael Irizarry's group at the Biostatistics Department
of the Johns Hopkins University Bloomberg School of Public Health.
I completed a Ph.D. in Computer Sciences at the University of Wisconsin-Madison under the supervision of
Grace Wahba
and Raghu Ramakrishnan (now at Yahoo! Research).
My dissertation work was on computational analysis methods for graph-based data.
My current research interests are (1) analyzing gene expression and other transcription mechanisms, and (2) semiparametric risk models that combine genomic, environmental and relationship data in population studies. At Hopkins, I've been developing analysis methods for second generation sequencing data.
I also work on general methods for machine learning and data mining: kernel methods for predictive model building; mixed-integer programming for combinatorial estimation problems; theoretical results on semidefinite programming for model selection; classical database query optimization techniques for querying probabilistic data.
More detail on my research projects may be found here, but some highlights include:
- Probabilistic models for second-generation sequencing quality assessment, base-calling and mapping
- Extending Smoothing-Spline ANOVA models with pedigree data
- Tree-Structured Covariance Matrices for Gene Expression Analysis
