The Complexity Science Group is the only transdisciplinary group in complexity science in Canada. We tackle problems of structure, organization, and dynamics in diverse settings ranging from living systems and the Earth system to global computing and social dynamics. Particular examples are protein interaction networks, niche development in microbial communities, disease and rumor spreading, and dynamics of innovations (Paczuski, Grassberger
). Other examples include neuronal networks and the brain, extreme events and earthquakes as well as cardiac arrhythmia and, more fundamentally, nonlinear chemical reaction kinetics (Davidsen
). The latter is directly related to the work of the 2007 Nobel laureate in chemistry, physicist Gerhardt Ertl. We particularly look for avenues to "see across" different fields of inquiry to discover common principles that lead to nontrivial predictions.
One of our main interests is in empirically observable phenomena where heterogeneous structures emerge at macroscopic scales due to constituent microscopic entities and their underlying dynamics. We develop ways to characterize, classify and model such complex systems, and the procedures by which they are measured, using an empirically driven methodology that takes advantage of breakthroughs in high precision measurement and information technology. We use a broad range of tools from different parts of mathematical science to tackle the "complexity wall". These include graph theory, information and communication theories, agent based simulations, epidemic (or idea) spreading processes, nonlinear dynamics, statistical physics, probabilistic inference, and modern network theory.
Details on complexity science and our current research can be found under Research
and in this press release