My research interest is in statistical genomics. Microarray technology produces data on the expression levels of thousands of genes simultaneously but usually for a small number of replicated samples. So for this type of data, number of variables is much greater than the sample size. That creates a unique challenge for the statistical analysis and interpretation. Currently I am working on two research projects involving microarray data. One of the projects is a two-channel microarray experiment involving two strains of Salmonella enterica serovar Typhimurium. The second project involves identification of differentially expressed genes for the bacteria Bordetella Avium, which causes a highly contagious disease of the upper respiratory tracts of birds. In both of these projects I am working with Dr. Louise Temple of the Biology department. The second project is funded by the NSF grant (Interdisciplinary Training for Undergraduates in Biological and Mathematical Sciences (UBM)).

  I am working with Dr. Yuji Tomita of the Mathematics and Statistics department at James Madison University to develop a time series reversibility test based on a distance measure between the joint density function of the series and the series with reversed time indices. Dr. Jane L. Harvill of Baylor University and I are developing a bootstrap version of the bispectral based goodness-of-tests proposed in my Ph.D. dissertation. Part of the work has been already submitted for publication in Communications in Statistics: Theory and Methods.