Teaching

CIE 598 Data Analytics for Coastal Systems

This course introduces statistical methods for analyzing environmental data, where students develop R programming skills through hands-on work on processing real-world data from Maine's coastal environments. Emphasis is given in datasets such as sea level observations, wind speed and sea-surface pressure measurements, as well as seasonal temperature records. The course advances systematically from basic data visualization and descriptive statistics to predictive modeling, trend detection, probability distribution fitting via maximum likelihood estimation, and parametric uncertainty quantification. It culminates with the application of extreme-value theory for evaluating rare coastal events, particularly within the context of non-stationarity due climate change-driven sea-level rise.