Welcome!

I am a Ph.D. candidate in Economics at the University of California, Riverside. Over the past six years, my research has evolved from empirical studies to advancing machine learning and econometric theory, with a focus on causal inference.

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’m excited to share that I will be joining Uber’s Experimentation Team as a Scientist II in September.

My job market paper is available at Download Paper.

Research Interests

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

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