CEE520 Advanced Topics in Network Science: Graph Learning
This course equips students with techniques for supervised and unsupervised learning on complex networks. We explore statistical learning methods to infer clusters and predict links, introduce approaches to learn low-dimensional vector representations of graphs, and discuss deep learning applications to complex networks.
CEE420 Networked Infrastructure Systems
This course addresses the complexities of civil infrastructure systems, increasingly challenged by rapid urbanization and climate change. It integrates engineering principles, mathematical concepts, and computer science, equipping students with the necessary skills for designing and maintaining infrastructure systems. Lectures and exercises cover graph theory, network flows, hidden Markov models, Markov decision processes, neural networks, reinforcement learning, and graph learning, with applications for power, road, railway, water, and sewage networks.