I have long standing interest in Statistical Genetics. My methodological, computational and collaborative work address high-throughput genomic data. I am primarily interested in development and application of statistical methods to human genome data sets to identify genes determining complex diseases and phenotypes. I was motivated in methodological and computational development toward current direction while doing my MS in Mathematical Statistics under supervision of Mir Masoom Ali. My methodological development was reinforced, along with collaborative work, during my PhD research under the direction of Eleanor Feingold in the Department of Biostatistics at University of Pittsburgh. The main focus of my dissertation thesis was to develop a regionally smoothed meta-analysis method for GWAS data sets. I also developed human meiotic recombination scoring method for complex pedigree structures.
Currently I am working with Terri Beaty and Ingo Ruczinski as a postdoctoral fellow in Johns Hopkins Bloomberg School of Public Health. My research interests intersect with statistical genetics, genetic epidemiology of complex diseases, and bioinformatics. Currently I am involved with different collaborative studies on genetic epidemiology of oral cleft and a study of chronic obstructive pulmonary disease. My primary objective is to develop statistical and computational methods for different types of high-throughput genomics data including targeted sequencing data, whole exome sequencing data, and whole genome sequencing data.