Systems-level Analytics

I draw on over a decade of data analytics and statistical programming to identify meaningful patterns in complex systems and drive data-driven decision making. I currently consult with the Research & Planning (RP) Group, a non-profit, non-partisan research team that supports student success and equity for the California Community College systems. I use my background of bioengineering, disease ecology, and epidemiological statistics to rigorously analyze "black box" systems and draw actionable conclusions on their inner workings.

Heat map of San Francisco displaying ZIP-code-based student residence data

Supporting Community College Students with Data

As an institutional researcher, I work to support community college student equity and success. I currently consult with the Research & Planning (RP) Group, a non-profit, non-partisan research team, to support state-level policies that promote equitable student outcomes. I previously worked with the Office of Research and Planning at the City College of San Francisco to visualize data and empower faculty and staff to make evidence-based decisions.

COVID-19 and Income Inequality

For my Master's Degree in Ecology and Evolutionary Biology, I examined the the infection fatality rate (IFR) for COVID-19. This interactive demo examines the relationship between IFR, age, and income (measured as median income or income inequality) on a country level. United States data was inferred using a Bayesian statistical model.

Theoretical Models of Bioengineering for Global Health

For my Bachelor's honors thesis in Bioengineering, I studied the relationship between genetic engineering and global health. This theoretical model examines the potential application of a CRISPR-Cas9 gene drive to a population of Biomphalaria glabrata snails, the intermediate host for the neglected tropical disease schistosomiasis.

Disease Modeling

I love finding ways to turn theorectical concepts into interactive teaching tools. This interactive demo shows different outcomes of large-scale pandemics by walking the user through different compartmental epidemiological models.