The focus of my research is developing statistical methodologies for genetic mapping of complex traits. In particular, I have developed trait-model-free approaches for linkage detection using extended pedigrees. My general interest includes computational statistics, parametric and nonparametric inferences and their application in different areas of statistical genetics.Currently I am working on modeling heritability, association between multiple variants (both rare and common) and single or multiple traits in case-control/cohort or in family studies . My methodological research is supported by NIH/NIDA R01 and NIH/NIDDK R21. I am also involved as a co-investigator in several R01s led by faculty in Epidemiology and Psychology. My collaborative work involves addressing statistical issues in pedigree-based or cohort-based genome-wide association studies. I have developed and applied my methods to a variety of diseases, including type 2 diabetes, Alzheimers, kidney allograft rejection, substance abuse, venous thrombosis, and graft-versus-host disease post hematopoetic stem cell transplant.

I am currently the co-director of a statistical genomics training grant. More information about the training program can be found here

Chair, American Statistical Association - Section on Statistics in Genomics and Genetics, 2020.

Elected Fellow, American Statistical Association, 2017.

Standing member of NIH BMRD study section, 2017-2021.

Young Investigator, International Indian Statistical Association, 2016.

Fall 2013, 2015, 2017, 2019: Statistics in Human Genetics and Molecular Biology (PUBH 8445)

Fall 2008, 2009, 2010,2011,2012: Probability Models (PUBH 8432)

Spring 2007,2008 2014: Biostatistics I (PUBH 6450)