Complexity Science: Urban and Social Systems
This by-invitation-only event will bring together researchers in the field of complexity science with a focus on urban and social systems. Participants will present how the findings and methodologies of their research uncovers the hidden key parameters and properties of urban and social systems. The workshop will focus on how these key parameters can be found and how they can be used to improve systems, how small tweaks to them might change the dynamics and patterns the complex systems exhibit, and what it would take to use this knowledge in the real world.
The aim of the workshop is to bring together scholars from the field of urban complexity science to share ideas and information about their research. Non-linearity of complex systems will be the main focus. Specifically, how complexity science can identify key properties in urban systems that, with a small adaptation, can improve the whole system significantly. If policy making could be improved by this knowledge, they will leverage the little resources that are often allocated to them and have a higher benefit to all inhabitants.
The objective is to conclude the workshop with a clearer picture of ongoing research in urban complexity science and possible connections to policy making and urban planning. We consider it as a first step towards building a global network of urban scholars who want to think about possible implications their research has on urban systems and how their findings could be implemented.
Wednesday and Thursday, March 27-28, 2019
Christa Brelsford, Liane Russell Fellow at Oak Ridge National Laboratory
Daniel joined the Mansueto Institute for Urban Innovation in 2017 after completing his MSc in Computer Science and doctoral studies in Architecture/Urban Planning from ETH Zurich. He is enthusiastic about researching the fundamental laws of urban systems and their application to the real world. His goal is to find properties that can improve the quality of life in cities with minimal intervention. His previous work focused on the development of tools to support the urban planning and decision-making process, taking non-linear, self-organizing dynamics into account. The tools have been applied in different large-scale projects in Switzerland and Singapore. Daniel has been a lecturer at ETH Zurich, worked for different companies as a software engineer, and built his own startup company.