About Me
Applied Economist & Data Scientist
Public Health, Health Policy, and Data Science
I use econometrics, causal inference, machine learning, and predictive analytics to study population health, healthcare access, aging, food insecurity, and public policy.
I am an applied economist and data scientist whose research focuses on public health, health economics, aging, and policy evaluation. My work combines causal inference, econometrics, machine learning, and data visualization to examine how policies, economic conditions, and social factors influence health and well-being.
My research has examined food insecurity, diet quality, aging, family transitions, child well-being, substance-use policy, and related public health outcomes. I am especially interested in using large administrative, longitudinal, and survey datasets to generate evidence that can support healthcare organizations, policymakers, and communities.
I currently serve as a Visiting Assistant Professor in the Department of Business and Economics and the Department of Computer and Information Science at Allegheny College. I teach economics, statistics, data science, databases, and quantitative research methods.
Public Health Research
Health economics, aging, food insecurity, and population well-being
Policy Evaluation
Causal inference and econometric analysis of health and social policy
Data Science
Machine learning, predictive analytics, and data visualization
Research Focus
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Health economics, aging, and population health -
Food insecurity, diet quality, and health outcomes -
Health and social policy evaluation using causal inference -
Machine learning and predictive analytics for healthcare and public-sector decision-making
What I Do
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Public Health & Health Economics
I study how economic conditions, household transitions, public programs, and health policies affect nutrition, aging, behavioral health, and population well-being.
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Causal Inference & Policy Evaluation
I use difference-in-differences, event studies, fixed-effects models, and related econometric methods to evaluate health, education, and social policies.
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Machine Learning & Predictive Analytics
I develop interpretable models for risk prediction, population health analysis, institutional planning, and data-informed decision-making.
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Health Data Analysis & Visualization
I transform administrative, longitudinal, and survey data into clear statistical findings, dashboards, visualizations, and policy-relevant insights.
