Qijun Zhu
Qijun Zhu
Graduate Research Assistant
Experimental Economics; Behavioral Economics; Human and AI Decision-Making; AI Delegation; LLM Behavioral Evaluation
Qijun Zhu is a Ph.D. candidate in Economics at George Mason University and a graduate research assistant at the Interdisciplinary Center for Economic Science. He studies human and AI decision-making using economic theory, behavioral experiments, and meta-analysis.
His research connects deliberate strategy search with learning from feedback to explain how people choose and reset strategies. His work on AI delegation examines how evaluating both parties' welfare or representing one participant shapes AI behavior. He also develops reproducible methods for AI-assisted evidence synthesis. He is independently building LLM Behavioral Profile, a platform for measuring and comparing AI behavior.
Current Research
Whose Welfare Does AI Maximize? Decision Perspectives in Economic Games: Evidence from a Meta-Analysis and LLM Experiments. Sole-authored working paper.
Optimal Search in Multi-period Public Goods Games. Working paper with Kevin A. McCabe.
Grants and Fellowships
Interdisciplinary Center for Economic Science (ICES) Ph.D. Fellowship, George Mason University, 2021–2027.
Courses Taught
ECON 100: Economics for the Citizen — Instructor, George Mason University, Summer 2024 and Summer 2026.
Education
Ph.D. in Economics, George Mason University, expected 2027.
M.S.E. in Financial Mathematics, Johns Hopkins University, 2020.
Bachelor's degree in Statistics (Finance), Shandong University, 2019.
Recent Presentations
Cooperation, Trust, and Fairness with Generative AI: A Two-Block Meta-Analysis in Classic Economic Games.
Society for Judgment and Decision Making (SJDM), Annual Meeting. San Diego, CA. November 20–22, 2026. Upcoming presentation.
Cooperation, Trust, and Fairness with Generative AI: A Two-Block Meta-Analysis in Classic Economic Games.
Economic Science Association (ESA), North American Meeting. Charlottesville, VA. October 29–November 1, 2026. Upcoming presentation.
Optimal Search in Multi-period Public Goods Games.
Washington Area Meeting of Economic Scientists (WAMES). Arlington, VA. April 10, 2026.
Cooperation, Trust, and Fairness with Generative AI: A Two-Block Meta-Analysis in Classic Economic Games.
Association of Private Enterprise Education (APEE), 50th Annual Meeting. Las Vegas, NV. April 7, 2026.
Optimal Search in Multi-period Public Goods Games.
Southern Economic Association (SEA), 95th Annual Meeting. Tampa, FL. November 22, 2025.