Rui Shen

Built an end-to-end R-based analysis pipeline and package to handle diverse cross-sectional and longitudinal datasets, improving modelling completeness and computational efficiency. Implemented modular statistical and machine-learning methods, enabling flexible model comparison and extension. Designed simulation studies and empirical case studies to benchmark methods, assess robustness, and validate performance on real-world datasets. Produced comprehensive documentation and user guides to support knowledge transfer and maintainability.

Updated an R package implementing statistical methods for pooled testing; conducted extensive literature reviews, algorithm reproduction and validation, and case study analysis to ensure accuracy and applicability.

Discussed advanced statistical topics weekly and translated complex theories into accessible insights with real-world examples and interactive discussions. Presented topics including high-dimensional non-asymptotic and asymptotic statistics to interdisciplinary audiences.