Algorithms, Dynamics and Information Flow in Netzworks)

(Research Unit, funded by DFG, 2020-2023)

Spreading processes in networks are a central challenge in many areas of modern society - viruses spread in a population, news and opinions in social networks, malware in the Internet, etc. In financial markets, similar effects can lead to instability and bankruptcy and highlight the systemic risks in interconnected economies. Dynamics and spreading can also be used constructively, e.g., in the design of distributed algorithms for decentral applications. Dynamic spreading processes can be interpreted as an information flow in a network. In many applications, the fundamental algorithmic properties of these information flows are not well-understood. The research unit consists of six projects that study different aspects of spreading and information flow - distributed algorithms and population protocols, systemic risks in financial markets, learning and reconstruction, opinion dynamics, network design, and scalable algorithms for implementation and simulation of randomized processes. The goals are to establish foundational insights across the different areas, as well as to develop algorithms to simulate, reconstruct, control, and optimize information flows in networks.

Speaker: Martin Hoefer
Pls: Petra Berenbrink, Nils Bertschinger, Amin Coja-Oghlan, Tobias Friedrich, Martin Hoefer, Ulrich Meyer

Website of research unit: [Link]

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