Welcome!

I am a Ph.D. candidate in Economics at the University of California, Riverside, with six years of research experience ranging from empirical studies during my master’s program to exploring machine learning and econometric theory during my doctorate.

My research reinforces my strong belief that integrating machine learning with econometric theory will transform the research paradigm in causal inference. This integration provides empirical researchers with powerful tools to explore causal relationships more intelligently and effectively.

I am excited to announce that I am entering the job market and welcome any opportunities to connect. Please feel free to contact me or connect with me on LinkedIn if you’re interested.

My job market paper is available at Download Paper.

Research Interests

My research focuses on Causal Inference, Econometrics Theory, Machine Learning (Prediction and Causal Inference) and Applied Econometrics. The primary researches in econometrics theory and applied econometrics are semiparametrics, nonparameterics and financial economics.

• CausalML
• Double Machine Learning
• Individual Heterogeneity
• Endogeneity
• Continuous Treatment Effect
• Social Network
• Tree-based Models
• Deep Learning
• Balancing Approach
• Stock Price Crash Risk