About Me
I am a PhD candidate in Economics at the School of Economics, Peking University. My research focuses on computational macroeconomics, artificial intelligence, and public finance. I use structure-informed AI methods to solve dynamic economic models and place AI agents inside economic systems to study technological change and policy.
My methodological work embeds feasibility constraints, state transitions, discrete choices, and conditional expectations directly into neural networks and reinforcement learning, with applications to heterogeneous-agent macroeconomics, sovereign default, and pension reform. My applied work studies AI diffusion, labor displacement, optimal taxation, inequality, and monetary emergence. I will be on the 2026–2027 academic job market.
Research Fields
Computational Macroeconomics; Artificial Intelligence; Public Finance.
Education
Peking University, School of Economics
PhD Candidate in Economics (direct entry from undergraduate); expected June 2027.
Peking University, School of Economics
Bachelor of Economics
Research Projects
NSFC Original Exploration Program
Macroeconomic model construction and policy evaluation using intelligent algorithms and agents.
NSFC Young Scientists Fund
Optimal real estate tax reform design: a quantitative study using a heterogeneous-household model.
Open Project, National Intelligent Social Governance Experimental Base, Peking University
AI-based macroeconomic theory, algorithms, and models: the Donghu scenario.
New Engineering Interdisciplinary Youth Project
The emergence and evolution of money through multi-agent learning.
Academic Service
Organizing committee member for the 2026 SMLE Annual Conference and the PKU–Zurich Summer School on Machine Learning and Macro-Finance, responsible for participant communication, schedule coordination, and on-site support.
Skills
Programming and computation: Python (PyTorch), Fortran, C/C++, CUDA, MATLAB, and OpenMP; parallel and GPU computing.
Languages: Chinese (native); English (academic communication and teaching).