Our research focuses on the structure and dynamics of complex social and economic systems. We mine and statistically analyse data to test hypotheses; build, calibrate and validate large-scale agent-based models; and develop mathematical frameworks to analyse social and economic systems. In a truly interdisciplinary fashion, our team leverages expertise in economics, statistical physics, political and social science, applied mathematics, statistics, engineering and computer science. We follow a data-driven modelling approach that combines insights from big-data analysis with the power of agent-based computer simulations and the strength of rigorous mathematical models. Our agenda is not oriented towards established methods, but towards unsolved problems. Multidisciplinary research is necessary to understand (i) emotional interactions, e.g. in online social networks, (ii) collective decisions, e.g. in parliaments, (iii) failure cascades and systemic risk, e.g. in trade and financial networks, and (iv) collaborations, e.g. between firms or scientists.
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