This course explores the theories, principles, and methods for analyzing spatiotemporal behaviors, with a focus on understanding patterns in human mobility, urban dynamics, and transportation systems (especially micro-mobility systems). Students will learn to apply computational techniques to geographic and mobility data, integrating concepts from transportation studies to examine how individuals and populations interact with their environment over time and space. The first part of the course introduces spatiotemporal behavior, while the second part involves case studies, analysis, and simulation of spatiotemporal behavior using methods such as agent-based modeling and machine learning.