High resolution and fidelity in measuring (epi)genetic variation is the foundation of precision cancer genomics. As a geneticist and computational biologist, my research is focused on bioinformatic innovations to improve the detection and quantification of intra tumor heterogeneity (ITH) from next generation sequencing (NGS) data, and leverage patterns of ITH to infer the evolutionary dynamics of human cancers.
During my research tenure, I have developed considerable expertise in algorithm design and statistical analysis of (epi)genetic data, as well as in the computational modelling of cancer, such as gene regulatory circuits and cellular automata models. My unique experiences and quantitative training have enabled me to conduct impactful research at the interface of cancer genomics, computational and systems biology. My goal is to continue to develop algorithms and computational methods that advance a mechanistic understanding of tumor evolution and that are accessible and broadly utilized by the cancer biology community.