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, temperature and sea-surface pressure measurements, as well as seasonal wind speed records. The course advances systematically from basic data visualization and descriptive statistics to predictive modeling, probability distribution fitting via maximum likelihood estimation, and parametric uncertainty quantification. It culminates with the application of extreme-value theory and trend detection for evaluating rare coastal events, particularly within the context of non-stationarity due climate change-driven sea-level rise.

Lecture notes will be periodically uploaded here. R code will be provided directly during class. If you spot any typos and/or errors, please do not hesitate to reach out for corrections at info@futurecoasts.group.

Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Exam #1 (Fall 2025)
Chapter 6
Chapter 7

CIE 115: Computers in Civil Engineering

This undergraduate course introduces civil engineering students to algorithmic design and computer programming using MATLAB. Students learn foundational skills in analytical thinking, problem decomposition, and flowchart development. The course covers numerical methods including differentiation, integration, root finding, and systems of linear equations, among others, with students implementing solutions using MATLAB code. Throughout the course, students are taught to leverage generative AI as a companion tool for debugging and faster code development.

More information coming soon...