Random graphs were used by Erdős to give a probabilistic construction of a graph with large girth and large chromatic number. It was only later that Erdős and Rényi began a systematic study of random graphs as objects of interest in their own right. In the early eighties the subject was beginning to blossom and it received a boost from two sources. First was the publication of the landmark book of Bollobás on random graphs. Around the same time, the Discrete Mathematics group in Adam Mickiewicz University began a series of conferences in 1983. This series continues biennially to this day and is now a conference attracting more and more participants. The next important event in the subject was the start of the journal Random Structures and Algorithms in 1990 followed by Combinatorics, Probability and Computing a few years later. These journals provided a dedicated outlet for work in the area and are flourishing today.

Analyzing data as graphs has transitioned from a minor subfield into a major industrial effort over the past 20 years. The World Wide Web was responsible for much of this growth. Researchers were originally trying to understand the behavior and processes underlying the web; now, research blends rigorous theory and experiments in analyzing data as a graph.

The aim of the program is to stimulate further theoretical and practical developments on graph algorithms and models that impact these domains. We expect wide interest, especially from North America, as the theory of random graphs becomes an important part of combinatorics and mathematics in general (for example, 3 out of 21 plenary speakers at the latest International Congress of Mathematicians (2014) use random graphs and probabilistic methods in their research: Alan Frieze from Carnegie Mellon University, Vojtěch Rödl from Emory University, Ben Green from University of Oxford; Endre Szemerédi from Rutgers University received the Abel Prize in 2012; etc.).