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ABSTRACT / In this talk, I will present an overview of research directions that I've been involved in over the course of the past years concerning data-driven models and simulations of complex social and technological systems.
Recently, I have taken a simulation-based approach to model important aspects of urban human mobility and estimate the effect of new technologies. In this talk, I will present an overview of some of the possibilities and challenges related to on-demand mobility solutions of today and tomorrow. I will discuss possible ways how autonomous vehicles of different form factor can affect urban mobility. We have shown that an adoption of shared and autonomous vehicles could lead to a significant reduction in the number of parking, a significant form of land use today, contributing to a transformation of urban space use. I will discuss further aspects of (semi-)autonomous mobility, including the potential of small form-factor vehicles to serve as an efficient mobility solution for short trips. I will then present related results on estimating the cost of competition and non-coordination in on-demand mobility markets regardless vehicle technology.
In the second part of this talk, I will present an overview of my ongoing research at the Complexity Science Hub, where I'm working on developing agent-based models of early human societies with the aims of understanding potential origins of increasing complexity and large-scale cooperation and competition.
BIO / Dániel Kondor joined the Complexity Science Hub as a PostDoc in May 2021. Before that, he worked at the Senseable City Lab at MIT and SMART FM in Singapore. He earned a PhD in physics with a focus on network and data science from the Eötvös Loránd University in Budapest in 2015.
Dániel has worked with diverse topics that focus on the analysis of large-scale geographically embedded phenomena, including the study of human mobility in various contexts. His current research focuses on large-scale, agent-based models of interactions among historical societies. His research interests include data-driven and agent-based modeling of complex social, economical, and technological phenomena.