Visual analytics for deep learning on collective behaviour networks

This project utilizes deep learning for graphs to analyze collective behaviour visually, for instance, to model and visualize mobility networks in collectives. The project's central research question is: How can machine learning for graphs promote the visual analysis of collective behaviour? The project aims to tackle the following three research challenges:

(1) graph representation learning for heterogeneous collective behaviour networks;
(2) the visualization of dynamic biological networks and network propagation;
(3) developing visual analytics systems that leverage deep learning models to explore large-scale evolving collective network data.