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Leihua is a Ph.D. Candidate in Political Science with a Master's degree in Statistics at the UC, Santa Barbara. As a Data Scientist, Leihua has six years of research and professional experience in Quantitative UX Research, Machine Learning, Experimentation, and Causal Inference.
His research interests include:
1. Field Experiments, Research Design, Missing Data, Measurement Validity, Sampling, and Panel Data
2. Quasi-Experimental Methods: Instrumental Variables, Regression Discontinuity Design, Interrupted Time-Series, Pre-and-Post-Test Design, Difference-in-Differences, and Synthetic Control
3. Observational Methods: Matching, Propensity Score Stratification, and Regression Adjustment
4. Causal Graphical Model, User Engagement, Optimization, and Data Visualization
5. Python, R, and SQL
