Stream Data Analytics and
Machine Learning laboratory

The innovative research in stream data and machine learning
led by the minds that envision and hands that shape the future of Big Data World.
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Stream Data Analytics

Up to 100 Gbit/s intellectual packets processing
Discover people behavior under traffic

Machine learning

Deep learning technique
FRiS-methodology and other kernel functions
Cutting edge face recognition technology
Speaker identification
Speech recognition
Text classification


True Data Scientist solves the problem by combining the hardcore science and breakthrough data mining technologies with inexplicable art of human understanding. We propse an unique combination of Deep learning technique with a strict explainability of original FRiS method. Function of Rival Similarity allows us to make discovered patterns undestandable, which makes it a competetive advantage in case of reasonable decision making.

Software Engineering

Storage Technologies, Project management, Python.

Business Analytics

Business Analysis, Business Scaling, Knowledge Management, Data Warehousing.

Deep Learning

Statistics & Algorithms, Machine Learning, Natural Language Processing, Artificial Intelligence, Decision-Making Theory, Signal Processing, and Deep Learning.


We provide an entry point to the network of hi-qualified companies and institutions of Siberian Branch of Russian Academy of Sciences.

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Evgeniy Pavlovskiy

PhD in Math, Leading researcher

Bair Tuchinov

Head of the laboratory

Ivan Bondarenko

Leading Researcher, NLP and Speech

Akilesh Sivaswamy

MSc, Research engineer, superpostition expert

Evgeniya Amelina

Ph.D. Scientific Researcher

Daniil Grebenkin

B.Sc., Research Engineer

Welcome to our team!


1. Sheng L., Pavlovskiy E. N. Reducing over-smoothness in speech synthesis using Generative Adversarial Networks // Data Science and Engineering (SSDSE), 2018 Siberian Symposium on. IEEE. — 2018. URL:

2. E.N.Pavlovskiy. Problems and prospectives of Big Data storage and processing standardization // Data Science and Engineering (SSDSE), 2018 Siberian Symposium on. IEEE. — 2018.

3. A. Sivaswamy, E.N.Pavlovskiy. Comparing Speech Classification of Russian digits by HMM and LSTM on small training set // Data Science and Engineering (SSDSE), 2018 Siberian Symposium on. IEEE. — 2018.

4. S.A. Alyamkin, N.A. Nikolenko, E.N. Pavlovskiy, V.V. Dyubanov. FRiS-censoring of reference sample in face recognition task by deep neural networks // Data Science and Engineering (SSDSE), 2017 Siberian Symposium on. IEEE. — 2017. URL:

5. Pavlovsky E. N., Pakulich D. V., Pospelov S. O. Restoration of the 3D Skull Defect Model Based on Deep Neural Networks. Vestnik NSU. Series: Information Technologies, 2017, vol. 15, no. 3, p. 74–78. (In Russ.) URL:


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