We build computational frameworks to model phenotypic heterogeneity across molecular, cellular, patient, and population scales.
Our research explores how modular alterations/perturbations in molecular networks propagate upward to shape cellular programs, define patient subgroups, and structure population-level variation. Across aging, metabolism, neurodegenerative, and pulmonary diseases, the unifying objective is to extract reproducible architecture from high-dimensional data.
Our aim is to formalize heterogeneity as a measurable and modelable property of health & disease.
We welcome inquiries from prospective students and researchers interested in computational systems biology of complex diseases.