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Pokrovsky boulevard, 11, room S938, Moscow, Russia, 109028
Phone: +7 (495) 772-95-90*27319
The School of Data Analysis and Artificial Intelligence was created in 2014 as part of the Department of Data Analysis and Artificial Intelligence. The school consists of world-renowned researchers who actively participate in international research projects.
Acquaye F. L., Kertesz-Farkas A., Stafford Noble W.
Journal of Proteome Research. 2023. Vol. 22. No. 2. P. 577-584.
Vasilii A. Gromov, Yury N. Beschastnov, Korney K. Tomashchuk.
PeerJ Computer Science. 2023. Vol. 9. No. .
Makhalova T., Kuznetsov S., Napoli A.
Data Mining and Knowledge Discovery. 2022. P. 108-145.
Dudyrev E., Semenkov Ilia, Kuznetsov S. et al.
Plos One. 2022. Vol. 17. No. 10.
Zhirayr Hayrapetyan, Nascimento S., Trevor F. et al.
In bk.: Information Systems and Technologies: WorldCIST 2022, Volume 2. Iss. 469. Springer, 2022. P. 141-147.
Dudyrev F., Neznanov A., Anisimova K.
In bk.: Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium -23rd International Conference, AIED 2022, Durham, UK, July 27–31, 2022, Proceedings, Part II. Springer, 2022. P. 436-439.
Egurnov D., Точилкин Д. С., Ignatov D. I.
In bk.: Complex Data Analytics with Formal Concept Analysis. Springer, 2022. P. 239-258.
Egurnov D., Ignatov D. I.
Automation and Remote Control. 2022. Vol. 83. No. 6. P. 894-902.
Kudriavtseva P., Kashkinov M., Kertész-Farkas A.
Journal of Proteome Research. 2021. Vol. 20. No. 10. P. 4708-4717.
Kanovich M., Kuznetsov S., Scedrov A.
Information and Computation. 2022. Vol. 287.
Academic Groups
The Laboratory of Intelligent Systems and Structural Analysis was created in 2012. The Laboratory conducts basic and applied academic research on analysing big data and complex data structures. The laboratory also develops software for analysing applied and research-related data. In addition, the lab is developing as a research centre and a platform for integrating the newest methods in artificial intelligence – with a special emphasis on intellectual data analysis and structural analysis – for raising ‘intelligence’ and making software adaptive.
- Methods of Texts’ Analysis and Visualization Research and Study Group, Academic Supervisor — Boris Mirkin, 2013
The aim of the project is to create methods for text visualisation on two types of tree-like structures – suffix trees (annotated with letters) and taxonomies (annotated with concepts) – using annotated suffix trees, approximation clustering and biclustering analysis, and an economical ‘lift’ in sets developed by the project manager or under his supervision. To do this, the following materials will be used:
- Materials from the Higher Attestation Commission (VAK) for the certification of scientific fields, as well as Internet resources such as Wikipedia. The aim is to develop an alternative taxonomy of mathematics and informatics, as well as their applications. This problem arose in connection with our previous project, since it became clear that the current taxonomy of mathematics in AJ Mathematics is not suitable for analysis purposes due to its fragmentation and imbalance.
- News materials from the Internet on the development of business processes in the country and its regions. Here we focus on our successful experience in analysing a thousand online documents. We managed to build a graph of the interdependence of key phrases. The graph reflects the main features of the business process in Russia in the relevant period of time.
- A collection of workers’ letters to the city administration about various housing, transport, and other problems. These letters were collected under the supervision of Professor Eduard Babkin of HSE Nizhny Novgorod. Here we focus on the taxonomy of problems. We constructed this taxonomy following the preliminary analysis of five hundred of such letters.