Randomness and learning in networks

Large Networks is one of the key notions in contemporary science and technology.

The availability of massive amounts of data and interaction between individuals of large populations of any kind, whether biological, social or computer units, places network analysis at the forefront of current scientific challenges.

The mathematical foundations of large networks have now become the focus of research in the later decades from diverse perspectives.

The project RandNET brings together leading researchers worldwide from the areas of combinatorics, probability theory, computer science and statistics with the aim of blending approaches from these areas in the rigorous mathematical foundations for analysing random networks. The whole project is driven by real applications in data science and learning on large networks.

This is planned through an alliance between academic and industrial partners.

A second goal of the project is to establish a wide platform of knowledge dissemination on the topic of randomness and learning in networks for use of specialists from all scientific disciplines.