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Grounded in first principles, my research develops algorithmic solutions for complex social systems at the intersection of artificial intelligence, economics, and statistics. One line of my research develops time-domain and frequency-domain approaches to dynamic equilibrium models with strategic agents. Another line develops Bayesian methods for estimating large-scale structural models. These tools are applied to study economic policy, asset prices, and social networks. Recently, I like to train neural nets regularized by economic theory. My previous research studies the evolution of cooperative and altruistic human behavior.

As an educator, I teach economics, statistics, and computer science with comprehensive open-source curricula on GitHub. I also co-founded Business School 101, a YouTube channel with over 100k subscribers democratizing business education. Beyond the classroom, I am a thematic investor for space economy and have rich experience in derivative trading.

Check out my channels on YouTube, Discord, and X for more, and email me if you have any questions. Feel free to sponsor (preferably via Dogecoin) the open-source content of this homepage.

• Learning the Macroeconomic Language [PDF], with Siddhartha Chib, manuscript, 2025
• Policy Rule Regressions with Survey Data [PDF], with Leifei Lyu and Zheliang Zhu, revised and resubmitted at Journal of Economic Dynamics and Control, 2025
• Forecasting the Forecasts of Others on Social Networks [PDF], with Leifei Lyu, manuscript, 2025
• Appetite for Treasuries, Debt Cycles, and Fiscal Inflation [PDF], revision requested at Macroeconomic Dynamics, 2024
• Rocket Lab Q3 earnings call [11/10/25]

• Profile: Curriculum Vitae, Research Papers, Google Scholar
• Courses: Game Theory, Neural Network, Bayesian Statistics, Macroeconomics, Monetary Economics, International Macroeconomics
• Affiliations: Saint Louis University, Business School 101, Insightful Minds in International Macro, Center for Economic Behavior and Decision-making

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