Research Interests

I develop machine learning and statistical methods for problems in biology and medicine. My focus is on using graphical models to represent complex relationships. I am interested in statistical methods, Bayesian models, stochastic models, and automated systematic explanation of these models.

Ongoing Research

Tree-based methods for black-box model explanation

The goal of this project is to develop an automated method for translating uninterpretable machine-learned models to interpretable decision-tree-like models with high fidelity.

Machine learning for metadata standardization

The goal of this project is to develop an automated method for standardizing unstructured metadata to existing ontologies.

Publications

A complete listing is available here and on Google Scholar.

Education

PhD	2014	Intelligent Systems	University of Pittsburgh, Pittsburgh, PA
MS	2011	Intelligent Systems	University of Pittsburgh, Pittsburgh, PA
BS	2008	Computer Science	University of Maryland, Baltimore County, Baltimore, MD
BS	2008	Mathematics	University of Maryland, Baltimore County, Baltimore, MD

Past Research

• Context-Specific Nested Effects Models

• Detection and Explanation of Statistical Differences Across a Pair of Groups

• Spatial Cluster Detection Using Dynamic Programming

• Pennsylvania-Ohio Biosurveillance Grid Project (PA-OH BiG)

• Modelling eukaryotic flagellar growth as a stochastic process