Model-based microeconomist focused on designing economic models that support decision-making and explain market behavior.

I currently serve as an Economic Modeling Advisor, where I develop and apply quantitative tools to help stakeholders assess complex economic systems. My work draws on computational techniques such as general equilibrium (GE) models, gravity models of trade, Bayesian methods, calibrated likelihood frameworks, and stochastic analysis. I focus on translating economic theory into practical tools that inform policy and strategy.

Previously, I worked as a Research Agricultural Economist at the USDA Economic Research Service, where I analyzed food systems and their implications for farmer welfare and human health. My research there examined how modeling assumptions influence our understanding of food markets.

I hold a Ph.D. in Agricultural and Applied Economics from the University of Illinois, with methodological expertise in Bayesian inference, likelihood-based estimation, and general equilibrium simulations.