Complex Systems & Network Science
Complex systems, together with network science, are a field of immense significance, due both to their foundational nature and also their wide interdisciplinary nature. Complex systems and networks are present anywhere and cover a huge variety of categories, such as systems biology, ecology, epidemiology, engineering, information systems, physiology, social and economic systems, statistical linguistics, urban systems, and many more.
Other researchers: Samuel L. Unicomb, Alina Dubovskaya
Applications of Stochastic Processes
Stochastic processes embody dynamic systems characterized by inherent randomness. We specialize in developing analytically tractable, high-dimensional stochastic models with realistic dependence structure for applications such as optimizing large derivative portfolios, effects of transaction costs on performance of actively managed funds, or information propagation in networks.
How opinions change and spread in systems is an important area in complex systems. We model this through mechanisms such as influence spreading and homophily on both simulated and empirical data. We perform both analytical calculations and Monte Carlo simulations using well studied agent-based models as well as diffusion in networks.