Last month, I attended the COSTNET19 Conference in Bilbao (Spain). This conference is organised by COSTNET, a COST Action which aims to foster international European collaboration on the emerging field of statistics of network data science. COSTNET facilitates interaction and collaboration between diverse groups of statistical network modellers, establishing a large and vibrant interconnected and inclusive community of network scientists.

As you can imagine, “statistics of network data science” is quite a big and diverse field, as it was the conference itself. And this is one of the things I really enjoyed, finding out how researchers from all around Europe are using similar methods to those I am using in my own work but applied to a completely different problem. The opposite scenario also applies: I realised that statistical methods employed to solve problems in other fields could also be used in my own research.

From my non-mathematical background, I would classify the different talks and posters that were presented during the conference in two groups: mathematical talks were some fancy mathematical approach was described and explored from a theoretical point of view; and really applied talks in which despite not having a strong and interesting mathsy content, they used statistical approached to really specific (and interesting!) datasets. Some of these talks were about the patient movement network in Norwegian hospitals (G. Scalia-Tombia, University of Rome Tor Vergata), the analysis of public transport in Berlin (R. Hilman, Central European University) or the Analysis of Corruption Networks in Public Procurements across European countries (S. Fierascu, Central European University).

I really enjoyed the conference, not only because it was in Spain (great food and weather!) but also because of all the people from different European countries that I met there and that let me know a bit more about their research. I also presented my own work. But I guess that will be the content for the next blogpost.