Biography

I grew up in Rockville, MD USA, and attended Johns Hopkins University where I double majored (Bachelor of Science) in Biomedical Engineering and Applied Mathematics and Statistics. I then completed my Master of Science in Engineering in Biomedical Engineering at Johns Hopkins University with a concentration in biomedical data science. During my time at JHU, I realized that the information age we live in allows for data-driven innovation. After graduating from JHU, I began working as an associate computational biologist at the Broad Institute of MIT and Harvard. During my time at the Broad, I gained a lot of experience working with omics data to derive biological insight.

During my PhD in Biostatistics, I will formalize high-dimensional causal discovery and inference, leveraging machine learning techniques such as Differentiable Causal Discovery and graph neural networks. I will apply these methods to biological datasets for an improved understanding of gene regulatory networks and personalized medicine, addressing the gaps in current statistical methods used in research. This research is important as it will refocus data analysis on what researchers are primarily interested in, causal relationships.

Previous Education

Johns Hopkins University Applied Maths and Statistics 2022
Johns Hopkins University Biomedical Engineering 2022