Visual Analytics for Large Networks: Theory, Art and Practice
Artificial Intelligence/Machine Learning
This session WILL be recorded.
TimeThursday, 12 August 20214:30pm - 5pm PDT
DescriptionThis course introduces the audience to the field of visual analytics for large networks. The course starts from the basics and builds on that foundation, showcasing much of the critical state-of-the-art and ongoing cutting-edge research in the field.
Prerequisites No prerequisites are strictly necessary, but some background in data visualization, graph theory, or computer graphics would be useful.
Intended Audience The material presented in the course is aimed at an intermediate-level, primarily at practicing computer scientists, but it includes enough introductory material not to alienate a less-expert audience. For the visualization expert, the course will introduce them to the state of the art in immersive visualization and enable them to apply the material directly to their work. The less expert audience will get a primer in graph theory and practical techniques for community detection, layout optimization, immersive visualization, and data visualization's importance more broadly.