Milton Friesen’s work includes serving on the executive team of Cardus, a public policy think tank, in addition to pursuing a Ph.D. at the University of Waterloo, School of Planning. He has had diverse leadership and research experience that includes local and national non-profit contexts, elected municipal service, corporate communications work, undergraduate teaching as well as research and policy development.
His current research interests involve networks, cities, imaging, and planning policy.
The rapid increase in computational speed, capacity and sophistication is changing the way people interact with each other and with the environment around them. Planners and researchers can model potential building and city designs, analyze data about myriad types of human interactions, economic factors, demographics and measures of well-being in any number of ways.
Complexity science and network science can be combined with data visualization and modelling to generate more sophisticated and useful insights for long-term vitality in cities and regions. Open data is becoming increasingly common and new sources of data are springing up every day. Making sense of this information is absolutely critical and will require new approaches, deeper collaboration, and significantly more ingenuity than we are used to generating.
One specific area he has been exploring involves new ways to map and visualize the relational fabric of a city – social imaging. Significant amounts of data exist about individuals. We know less about the dynamic space of relational patterns. We have a significant amount to learn about the social networks that exist in a given region, city, census tract or neighbourhood. The real-world relationships that represent very significant dynamics in our cities remain under-studied as are the new institutional forms that are emerging in this space. Approaches that involve significant human impact analysis are very much needed to enrich what is already being done.
Tagged with: adaptive networks • agent-based modeling • collective behavior • cooperation versus competition • dynamical networks • network game theory • networks • nonlinear dynamics • scale-free networks • self-organized criticality • social dynamics • social network analysis • spatial game theory