Research

Master’s Thesis

Reasoning About AI-Assisted Opponents: AI Advice and Counterpart-Advice Information in a One-Shot Beauty Contest

*University of Amsterdam · MSc Business Economics (Neuroeconomics) · 2026 *

This project examines how AI-generated advice and information about an opponent’s access to AI advice influence strategic reasoning and decision-making in a one-shot beauty contest.

More broadly, I am interested in how people interpret algorithmic advice, form beliefs about human and AI decision-makers, and adjust their choices in strategic environments.

Research Experience

Research Assistant · Johns Hopkins University

Applied Microeconomics & Corporate Finance · May 2024 – Jun 2025

Conducted empirical research on firms’ financing decisions, monetary-policy communication, and asset-price responses. My work involved large-scale SEC filing data, textual analysis of FOMC materials, and econometric analysis using Python and Stata.

Research Assistant · Carbon Offset Project

Environmental & Applied Microeconomics · May 2024 – Nov 2025

Worked with large project-level datasets on carbon offset initiatives, focusing on data linkage, measurement, and empirical analysis of project costs and characteristics.