Networks & Complexity

Complex networks are the central theme tying together most of my research activities to date.

I initially became interested in complex networks (and complexity more generally) in the final year of my undergraduate studies in theoretical physics, during which I developed an algorithm for the spatial embedding of networks. What drew me especially to networks is their applicability to a wide range of systems. Indeed, a great variety of phenomena, both natural and man-made, can be viewed and modeled as networks. Our brain is a network of neurons, each of which relies on a complex network of chemical interactions between its constituent molecules. The World Wide Web is a network of hyperlinks between sites, our friendships constitute social networks, we travel on public transportation networks and catch diseases that often spread on a network of person-to-person contact.

Although I have since specialized in the study of brain networks (at the micro and macro scales), I maintain a strong interest in broader questions about dynamical processes on networks, as well as the dynamics of time-evolving networks and, most recently, questions of network visualization.

I believe that there is much to be gained from maintaining strong links between researchers applying the tools of network science in a variety of disciplines. It is in this spirit that I co-founded the Cambridge Networks Network (CNN), a forum for academics across different fields who share an interest in Complex Networks. I am currently building a ‘resources’ page for CNN, with links to useful software, datasets, conferences, blogs, etc related to network science.