Hsei Di is a data analyst and researcher in the Epidemiology for Practice and Policy Group. She is experienced in data linkage (integration), machine learning techniques, epidemiological study design and data analysis, particularly those that use whole-of-population linked data. Her current and past projects include topics such as emergency hospital readmissions, Medicare out-of-pocket costs, and large-scale environmental contamination from loose-fill asbestos and per- and poly-fluoroalkyl substances (PFAS).

Hsei Di is also concurrently undertaking an MSc (Computational Data Analytics) at the Georgia Institute of Technology.

Research Interests

• Large-scale linked administrative datasets
• Longitudinal data analysis