Ariel M. (she/her)

I'm a computational biologist building mechanistic and data-driven models to understand and treat disease. My work spans molecular, cellular, and organ-level systems, and I build models in close collaboration with experimental teams.

My PhD research at the University at Buffalo focuses on how estrogen loss during aging drives inflammation in the gut and immune system, contributing to bone disease. To identify critical mechanisms of inflammation and bone loss, I build ODE-based models of immune cell population dynamics in response to hormonal and dietary changes. I also analyze bulk RNA sequencing data from collaborators to characterize how the gut environment changes across conditions. I estimate cell populations to inform the ODE models using deconvolution, which requires curating a single-cell reference from existing public datasets, since none are close enough biological matches on their own.

Before graduate school, I spent two years as a materials scientist at Lawrence Livermore National Laboratory doing R&D for laser-based physics experiments. Throughout, I found myself drawn to data analysis and computational approaches, attending seminars that showed me how models could complement and accelerate experimental work — eventually leading me into computational research.

I'm currently working on my dissertation and targeting graduation in summer 2027.

I'm looking for research scientist roles in quantitative and systems biology where I can build and leverage computational models alongside experimental teams. If you're in this space, I'd love to connect.