Expertise: Statistical modeling, statistical computation including parallel and high performance computing, programming in R and Python; applications to physical and biological sciences, health services research, administrative claims data.
Degree: PhD in Statistics, University of Michigan
James has provided statistical expertise to a variety of projects, particularly in biomedical domains. While a post-doc at the UM Cancer Center, he extensively used advanced bioinformatic and statistical tools for large-scale data analyses. His research interests include structure learning for biological networks, especially from perturbation or time-series data, and enrichment analysis. Other areas of expertise include: regression modeling, graphical models, high performance computing, inter-rater reliability, and parameter estimation for dynamic systems.