TEACHING
Mobility Modelling
This course overviews fundamental topics in mobility modelling and urban dynamics from a modern perspective. The course's main objective is to use data to understand how, when, where, and eventually why people move. By analysing mobility's short-term and long-term impacts on the environment and society, we focus on transitioning from the traditional vehicle-centric vision in transportation and mobility modelling to a human-centric one.
Intelligent Transportation Systems
This course provides an in-depth exploration of intelligent transportation systems, focusing on core principles of systems integration and technology implementation. Students will gain insight into the fundamental concepts and key technologies in sensing, communication, and data management, and learn techniques for system evaluation. Topics covered include automatic vehicle location and identification, dynamic control systems, travel information systems, and incident detection systems. Additionally, the course offers an overview of ITS products and services, while addressing economic, social, and environmental considerations associated with ITS implementation.
Design and Analysis of Algorithms
The primary objective of this course is to familiarize students with algorithmic thinking and reasoning. By the course's conclusion, students will be proficient in analyzing the asymptotic running times of algorithms, explaining the major design techniques employed in algorithm development, crafting precise proofs to establish the correctness of algorithms, and creating efficient algorithms to address various engineering problems.