This week I attended Stochastic Networks 2018, which took place at the International Centre for Mathematical Sciences (ICMS) in Edinburgh, Scotland. I presented a poster at this conference, and I was awarded a small prize for it.
Stochastic Networks conference
Here is its description, taken from Stochastic Networks 2018’s website:
The focus of this week-long conference will be analysis of stochastic networks and their applications, which includes modelling, stability analysis, control, performance analysis and design of stochastic networks. Such analysis requires the bringing together of ideas and methodologies from a range of mathematical disciplines, including applied probability, stochastic processes, operational research, combinatorics and graph theory. The meeting will cover a diverse range of application areas from those which have traditionally been studied using stochastic networks, for example telecommunications, call centres and manufacturing networks, to more novel areas, for example power systems, social networks, neural networks.
Stochastic Networks is one of my favorite conferences. First of all, it is a small conference – there were approximately 75 attendants. Second, the conference only invites expert speakers from around the world. These speakers are asked to present an overview of their research progress over the last three to five years. Their talks are therefore always intriguing and very complete. It is also always nice to visit new places, and see interesting sights.
Poster session and a small prize
This year, the conference had a poster session. I submitted a poster titled Optimal Clustering Algorithms in Block Markov Chains, which is based on my post-doctoral research with Alexandre Proutiere. I have uploaded the poster right here for you if you are interested:
In total there were 25 posters and out of those, the Programme Committee selected 5 posters. They then awarded books to their authors. I was lucky enough to be awarded the book Pierre Brémaud – Discrete Probability Models and Methods: Probability on Graphs and Trees, Markov Chains and Random Fields, Entropy and Coding! Books are absolutely great and I will definitely read it 🙂