SEMSTAT: Statistical Network Science

History of SemStat

The SemStat were initiated by Ole E. Barndorff-Nielsen, Wilfried Kendall and Gerard Létac in 1989, as a meeting at which high-level expository talks would be presented on new developments in statistics, with the objective of promoting a “European School of Statistics”. They wanted to emulate for statistical science the success of the Strasbourg Probability Seminar and the Saint-Flour Summer school (which both have had a big and continuing impact on probability from the 60's till today). As a result of each SemStat there is a conference volume of expository articles based on the main talks. Since August 1996 SemStat takes place under the auspices of the European Regional Committee of the Bernoulli Society for Mathematical Statistics and probability. Since 2016 the Lecture Notes of the SemStat meetings are published in an innovative Elements publishing scheme prior to the meeting by Cambridge University Press.

 

Aim of Short Course

A major challenge in many modern economic, epidemiological, ecological and biological questions is to understand the randomness in the network structure of the entities they study: for example, the SARS epidemic showed how preventing epidemics relies on a keen understanding of random interactions in social networks, the financial crises in 2008 arose from structural changes in the financial lending network induced by the subprime mortgage collapse, whereas progress in curing complex diseases is aided by a robust data-driven network approach to biology.

 

The aim of this short course is to introduce particularly early career researchers to the field of STATISTICAL NETWORK SCIENCE.

Two lecturers will each from their unique perspective introduce various aspects of network modelling and inference.

- Eric Kolaczyk's (Boston University) research interests revolve mainly around the statistical analysis of network-indexed data, with particular focus on both foundational issues and applied network problems.
- Alberto Roverato (University of Bologna) is interested in processes that occur on networks or, more specifically, graphs. He has made fundamental contributions to the field of graphical models and used them in reverse engineering of molecular regulatory networks.

 

Specifically for this course, the two lecturers have written two books, to be published by Cambridge University Press in February 2017.

 

For more information visit the website of Eurandom.