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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

Professors named among World’s Top 2% of Scientists
Professor of Russian Academy of Sciences Denis Sidorov and Professor of Henan Academy of Sciences (China) Samad Noeiaghdam have been recognized in the prestigious "World's Top 2% Scientists" list in fields of General Mathematics and Energy, compiled by Stanford University and published by Elsevier. Congrats!
The paper is accepted for ICEMS-2025
The manuscript "Impact of Greedy Energy Storage Operation on Power System Stability: A Prosumer-Centric Approach" by Beopsoo Kim, Nikita Rusetskii, Denis Sidorov, and Insu Kim is accepted for ICEMS-2025
Work of Minh Hien Dao was nominated for Guan Zhao-Zhi Award
Research article of Mr Minh Hien Dao et al "A Novel SoC Estimation Approach Using Kolmogorov-Arnold Networks with Shapley-Based Interpretability" was nominated for Prof. Guan Zhao-Zhi Award on CCC conference, China.