Scalable Visual Analytics for Uncertain Dynamic Networks

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Technological advances have provided a data deluge over the past few years, and have led to many large uncertain and dynamic network models. This includes terrorist networks, marketing networks, facebook networks, various biological networks, and software engineering structures. Human understanding of such networks is difficult. This project aims to provide new methods for visual analysis of large uncertain dynamic networks such as these. The algorithms developed in the project will help security analysts to monitor illegal behaviour such as money laundering and terrorist activities, help biologists understand key biological systems, and help engineers to understand large software systems.