Laboratory of Algorithms and Technologies for Networks Analysis
Laboratory of Algorithms and Technologies for Networks Analysis (LATNA) was created in 2011 at HSE Nizhny Novgorod. It secured research grants to extend its work beyond the initial three year project – among other funding it received a grant from the Russian Science Foundation for working on the project “Clustering and Search Technique in Large Scale Networks”. The HSE Lookis glad to continue the talk with LATNA from the April issue in which Panos Pardalos, laboratory’s Scientific Advisor shared his impressions from the XVI April International Academic Conference on Economics and Social Development and told about the laboratory’s workshop on data analysis methods.
What is the focus of the laboratory’s research and its applications?
Panos Pardalos, University of Florida, Distinguished Professor of Industrial and Systems Engineering, Scientific Advisor of the Laboratory of Algorithms and Technologies for Networks Analysis at HSE Nizhny Novgorod
Our laboratory focuses on how to analyze large data sets and networks. Everybody collects data these days but many do not know what to do with it – it’s like having a lot of books but not knowing how to read them. A lot of data is “noisy” and has errors, and cleaning data is one of the big challenges. We also work on many mathematical problems behind the techniques of analyzing data. For instance, we work on such famous combinatorial discrete problems as the maximum clique and graph theory - they have a lot of applications, especially in social networks. Two years ago I was a co-editor of a two-volume Handbook of Optimization in Complex Networks, and one volume is devoted to social networks, and another – to theoretical aspects.
Networks are applicable to all branches of science. They appear in biological research (biological networks, protein interaction) and computational neuroscience (brains are made up of the neurons and the dynamic connections between them). Social networks – like Facebook – are useful for studying how the news move around, how people share the information. At the laboratory we are also very interested in how different networks cooperate with each other and converge.
Valeriy Kalyagin, HSE Tenured Professor, Head of the Laboratory of Algorithms and Technologies for Networks Analysis
We also work with specific companies: for example, we use network analysis to help address the routing and logistics issues, or we work with analyzing large datasets, which is useful for IT companies.
The laboratory is situated in Nizhny Novgorod HSE branch but it also has good connections within other campuses of HSE: for example, this spring I gave a talk at the colloquium of the Faculty of Computer Science and one of our lab researchers and PhD students, Alexander Ponomarenko, was awarded the Ilya Segalovich scholarship from Yandex. We also plan a joint summer school with colleagues from St. Petersburg branch of HSE.
Panos Pardalos: Speaking of cooperation outside HSE, last year we organized two conferences: with the Institute of Information Transmission Problems of the Russian Academy of Science (RAS) and with Energy System Institute of the Siberian branch of the RAS.
Does the lab engage students into research?
Panos Pardalos: We have a lot of young people involved – PhD students, Master students, undergraduate students. We hope to attract more young people to the laboratory through the summer school: it provides the right environment for intensive learning and for engaging students in the research. Young researchers get a chance to receive good feedback from professors and other students.
When we just started the laboratory five years ago, we were teaching the students how to present the research results, and I can see how they’ve grown – they are confident, they go to international conferences. We see this as a success of the laboratory: young people really engaged into research and learned how to participate in the academic events.
The full text of the June issue of The HSE Look can be found here. For further information please visit ifaculty.hse.ru
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