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Welcome to Machine Learning, Computer Vision, and Dynamic Systems Group

Contributing to Future Energy using AI & Advanced Mathematics to make Affordable and Sustainable Energy

About Group

Our team has many years of experience in international (FP6, FP7, etc.), domestic (FTP, RFBR, RSF, etc.) scientific projects, as well as in a number of commercial R&D projects related to the processing and analysis of multidimensional data set. Group leader is Professor, DSc (Physics & Math) Denis N. Sidorov. Machine learning, computer vision and the theory of dynamical systems are closely related to the theory and methods of solving inverse and ill-posed problems, irregular integral and differential equations and constitute the main areas of scientific interests of our research group.

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Latest news

The manuscript “Part II: State-of-the-Art Technologies of Solar-Powered DC Microgrid with Hybrid Energy Storage Systems: Converter Topologies” was accepted to Energies
The review paper "Part II: State-of-the-Art Technologies of Solar-Powered DC Microgrid with Hybrid Energy Storage Systems: Converter Topologies" as part of the BRICS consortium ELISYUM (modELIng and control methodS of cYber-physical systems in mUlti-energy Microgrids) collaborative work was accepted to Energies SI Machine Learning for Cyber-Physic...Read more