Mike Lees

About the speaker

Mike Lees is an Associate Professor at the Universiteit van Amsterdam, where he leads the Computational Science Lab (Informatics Institute). He completed his Ph.D. Adaptive Optimistic Simulation of Multi-Agent Systems at and graduated from Edinburgh University with a joint honours Computer Science/Artificial Intelligence degree. His research is driven by scientific challenges in the area of social-urban complex systems and aims to develop novel methods in agent-based modelling (modelling methodology) and discrete-event simulation (computation execution). This includes methods for semiautomatic model construction, modelling formalisms that are able to capture human behavior and new ways to probe and measure social-urban systems to be able to validate and calibrate such models. His application areas include the growth of informal settlements, the process of school segregation through school choice, the dynamics of human crowds, and the social dynamics of EV charging behaviour. https://mhlees.com/


Social Complex Systems span a wide range of dierent application areas, but exhibit common systemic behaviours that emerge through the interactions of simple elements or individuals. This systemic behaviour can only be understood by holistic analysis that necessitates viewing the system as a dynamic collective of individuals.  As traditional means of quantitative analysis are known to be insucient to understand such systems, computational models are the only feasible means of analysis that are capable understanding such emergent phenomena. Many of these social complex systems present themselves where difficult policy decisions need to be made by governments (e.g., pandemics, segregation, infrastructure planning). In this talk I will present a collection of work (school segregation & electric vehicles) that has been done in close collaboration with different ministries and government departments to help manage and understand this complexity. I will explain how both theoretical models, as well as data driven models, play an important role in this process and show how such models can help change understanding and inform operational decisions of policy makers.