The Section for Science of Complex Systems, formerly Complex Systems Research Group (COSY), pursues quantitative complex systems research at the Medical University of Vienna - ranging from life science, quantitative social sciences, to applied mathematics and fundamental physics. The section is part of the Center for Medical Statistics, Informatics and Intelligent Systems.
Its research activities range from life science (artificial cells in silico, genomics, and analyzing biological times series) , to quantitative social sciences (measuring and modeling the dynamics of social interactions, financial markets, and bureaucracies), to applied mathematics and fundamental physics (statistical mechanics, network theory, systemic risk in complex systems, and the physics of evolution).
Stefan Thurner is team head and leader of WP4. He is currently Prof. for the Science of Complex Systems at the Medical University of Vienna, where he founded SSCS in 2003; External Professor, Santa Fe Institute; Fellow, Collegium Budapest. He holds PhDs in theoretical physics from the Technical University of Vienna and economics from the University of Vienna. He has published extensively in fundamental physics, applied mathematics, complex systems, life sciences, econophysics and most recently in social scientists. He is also active in consulting for financial institutions, especially about automated trading strategies.
Michael Szell is a postdoc research assistant at SSCS, with a PhD in computer science from the Technical University of Vienna. His scientific interests include simulation and analysis of complex systems, nonlinear dynamics, social network analysis and sociophysics, as well as econophysics and behavioral economics. He developed the MMOG Pardus in 2004 and has formed a company to manage the commercial aspects of the game.
Peter Klimek is a research associate at SSCS. He received his PhD from the University of Vienna in 2010. He has published on applications of physics to mathematical logic, sociology (opinion formation), political science (decision and policy making), administrative sciences (bureaucratic efficiency) and evolutionary biology (macroevolutionary dynamics).