The University of Texas MD Anderson Cancer Center
Department of Biostatistics
My research involves the development and application of novel statistical frameworks for analyzing complex and high-dimensional data in biomedical research, especially omic datasets arising from multiple platforms. The methodology focuses on various graphical models involving undirected and directed graphs, chain graphs, differential network inference, and network-based prediction. I am currently working on drug sensitivity data from cell lines and patient-derived xenografts and interested in constructing prediction models for understanding patients’ drug profiles using the cross-species genomic information. Students who complete a tutorial in my lab would experience analyzing big-data, multivariate data modeling, network modeling and data visualization, and gain programming skills in R.
Education & Training
Ph.D. - University of North Carolina-Chapel Hill - 2013