I am an applied statistician and biomedical data scientist working at the intersection of machine learning, computational omics, and population health. My research concentrates on developing statistically rigorous and computationally scalable machine-learning methods, as well as open-source software, that integrates population-scale multi-omics data to uncover functional mechanisms that explain disease heterogeneity.
Currently, I am a postdoctoral fellow in Biostatistics at Johns Hopkins Bloomberg of School of Public Health, mentored by Dr. Stephanie Hicks. I am open to opportunities that advance my scientific career.