Individuals and agents in many systems spontaneously organize to form structures such as flocks, swarms, and clusters. Investigating the principles that govern the formation and behavior of large groups in natural systems requires understanding the  structure of clusters, their connectivity, how their identities develop, and how information propagates. Similar goals are also important in statistics and machine learning for understanding massive clouds of high-dimensional data, where one relies on properties of graphs encoding data similarity. Likewise connectivity and structure play an important role in studies of network dynamics.

The goal of this workshop is to facilitate an exchange of ideas and methods among researchers from several disciplines studying groups, their structure and dynamics.