Introduction
Dirk Helbing is a physicist, and professor of sociology, in particular of modelling and simulation.
Biography
Dirk Helbing studied physics and mathematics at the University of Göttingen. He completed his doctoral thesis at Stuttgart University, on modeling social processes by means of game-theoretical approaches, stochastic methods, and complex systems theory. In 1996, he completed further studies on traffic dynamics and optimization.
In 1998 he became Managing Director of the Institute for Transport and Economics at Dresden University of Technology, and in 2000, became a full professor. In 2008, Helbing was elected as a member of the German Academy of Sciences Leopoldina. He heads the ETH Zurich Competence Center "Coping with Crises in Complex Socio-Economic Systems" and the "Physics of Socio-Economic Systems" Division of the Deutsche Physikalische Gesellschaft (German Physical Society).
Research activities
Dirk Helbing is known for the social force model, in particular its application to self-organising phenomena in pedestrian crowds. Besides the slower-is-faster effect, he introduced the freezing-by-heating effectand the phase diagram of congested traffic states. Helbing also proposed a microscopic foundation of evolutionary game theoryand has studied self-organized behavioral conventions. Recent work applies principles of collective intelligence and self-organized control to the optimization of urbanand freeway traffic. His current research activities focus on norms and conflict, the role of success-driven motion for the establishment of cooperation among selfish individuals, the science of science, socio-inspired technology and techno-social systems, disaster spreadingand crisis management.
Living Earth Simulator
He is the Principal Investigator on a project named FuturICT Knowledge Accelerator and Crisis Relief System, a computing system working on big datasets, conceived as sort of a crystal ball of the world. The core of the system is the Living Earth Simulator, a computing machine attempting "to model global-scale systems — economies, governments, cultural trends, epidemics, agriculture, technological developments, and more — using torrential data streams, sophisticated algorithms, and as much hardware as it takes". The project has lost in the final round of application for funding from the European Commission of €1 billion.