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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

Professor Denis Sidorov took part in the BRICS Contest as Foreign Expert
Professor Denis Sidorov took part in the BRICS Industrial Innovation Contest 2026 as the Foreign Expert. He participated in the "New Energy Industry" Track dealing with PV Technologies, Energy Storage Systems and Smart Energy. 30 projects from Cuba, Indonesia, Russia and China were presented.
The manuscript on Hammerstein IEs was accepted for the JIEA
The research by by V. Byankin et al. "Hybrid HAM-Neural Network Framework for Nonlinear Functional Hammerstein Integral Equations with CESTAC Validation" was accepted for publication to the Journal of Integral Equations and Applications. Congrats!
Two papers were accepted for IEEE Chinese Control Conference
Two manuscripts: "TKAN-Volterra Hybrid Model for Accurate Battery State of Health Forecasting" and "The Application of MPC for DC/DC Buck Converters" of PhD students M. Hien and V. Muratov were accepted for 45th annual IEEE Chinese Control Conference, congrats!