Dance events visitors exhibit traces of Lévy walks

Lévy walks are associated with (human) hunter-gatherer behaviour

Data driven methods for financial audits

Marcel Boersma (PhD candidate from KPMG and Computational Science Lab), Dr. Sumit Sourabh and Prof. Dr. Drona Kandhai of the Computational Science Lab, together with Aleksei Maliutin and Lucas Hoogduin from KPMG as industry partner, developed a novel data driven...

New publication in Scientific Reports

Britt van Rooij, Gabor Zavodszky, and Alfons Hoekstra publish a work on the formation process of platelet aggregates.

In-Silico Trials for Treatment of Acute Ischemic Stroke

Alfons Hoekstra et al. published a new paper in Frontiers in Neurology.

Group Mission

We live in a highly connected and strongly coupled world, and are surrounded by a large diversity of complex systems. All these systems have one thing in common: they process information. We aim to understand this information processing in such dynamic multi-level complex systems.

Can we detect and describe the computational structure in dynamic processes and can we provide a quantitative characterization of essential aspects of this structure? When modeling for instance traffic in a city, the interactions between the individuals driving the cars, the bicycles, and pedestrians result in a dynamic self-organizing interaction structure, which is superimposed on the road network. This can be seen as a dynamical computational structure where information is exchanged, stored, and processed. What are the essential aspects of this structure, and how do they determine the way in which information is actually stored, transferred, and processed in complex systems? And what does that mean for the overall system behavior, that is, for their emergent properties? Can we then better understand emergent properties and critical phenomena such as tipping points? For instance, where do traffic jams come from, which all of sudden seem to appear from thin air? Or, can we get a deeper understanding of the systemic economic crises that struck us in 2008? Are we able to steer or control such emergent properties? What can we do to prevent traffic jams while maintaining the throughput on the road? Maybe by bringing down velocity, or slightly controlling the traffic entering a road on the individual car level? Or more dramatically, can we ‘nudge’ the behavior of countries, large companies, and/or individuals to fight the climate change? The ever increasing and abundant availability of data, both from science and society, drives our research. We study complex systems in the context of methods like multi-scale cellular automata, dynamic networks and individual agent based models. The challenges include data-driven modeling of multi-level systems and their dynamics as well as conceptual, theoretical and methodological foundations that are necessary to understand these processes and the associated predictability limits of such large-scale computer simulations.

“Nature is a Complex System that processes information. Computational Science aims to make the complexity of those systems tractable.”

Twitter Feed (@UvA_CSL)

Hiring a 3-year #postdoc for the @AitionTo H2020 project! Join us on a quest and analyze real omics data to find: disease networks; multivariate statistics / synergistic interactions; and (hyper) network analyses. @UvA_CSL @LamersFemke

Short interview with Charles and myself on our INSIST project on In-Silico Trials for Stroke appeared in NeuroNews


PhD opening at the University of Amsterdam on the In-Silico modelling of late thrombosis on medical implants.


High shear platelet aggregation, combining in-vitro and in-silico, just published in Interface Focus.

@UvA_Amsterdam @bio_comp

Two great papers published dealing with multiscale modelling of brain circulation and perfusion, in the context of in silico stroke trials.

@UvA_CSL @INSIST33795864

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