Dr. Regmi is interested in understanding the individual genomic makeup and epigenetic architecture that can be tailored, as personalized medicine, to achieve more effective treatment of human diseases. His previous research investigated the familial association between rare variants of dilated cardiomyopathy and heart structure and function as measured by cardiac magnetic resonance and electrocardiogram techniques. 

In the Biodata Mining and Discovery Section at the NIAMS, Dr. Regmi has participated in several data mining projects related to autoimmune and skin diseases. He has contributed significantly to building bioinformatics tools and pipelines for workflow management, data processing, and visualization. He has written an R package called richPathR which is a valuable tool for mining and visualizing large numbers of gene sets. Recently, under the supervision of Dr. Hong-Wei Sun and Dr. Stephen Brooks, he has focused on building tools and algorithms related to statistical learning. These help researchers extract patterns from large genomic, transcriptomic, and epigenetic data.