Learning from the Interconnected World with Graphs

This lecture by the instructor covers the topic of learning from interconnected data using graphs. The content includes the challenges of machine learning with graphs, the design of Graph Neural Networks (GNNs), various research landscapes, and the democratization of Graph Machine Learning (ML). The lecture delves into the instructor's research on graph ML methods, interdisciplinary applications, and the development of tools like GraphGym. It also explores the impact of GNN design space, the application of GNNs in various domains, and the future vision of extending AI frontiers with graphs.