About Me

I am a sixth-year Ph.D. candidate at the Department of Economics, University of Washington. I'm honored to be advised by Prof. Yanqin Fan. My primary research interest lies in AI/machine learning (ML)-enabled causal inference and data analytics. Currently, I am also a visiting scholar at the Department of Information, Risk, and Operations Management, McCombs School of Business, The University of Texas at Austin, hosted by Prof. Ashish Agarwal.

I am interested in conducting research that applies novel data analytics to identify and solve challenging and practical problems that benefit businesses, healthcare, and society. I am particularly interested in exploring topics such as racial/gender disparity, fairness, and other related areas.

I’m interested in AI/ML-enabled causal inference from three angles: 1. Exploring new opportunities for using AI/ML to improve causal inference methodologies; 2. Identifying challenges in the current applications of AI/ML in causal inference; 3. Investigating innovative applications of generative AIs, from an empirical perspective.

My research methodologies include machine/transfer learning, causal inference, non-parametric estimation, and lab experiments. I am open to collaborating with researchers from various backgrounds in the future.