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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 novel ML based approach for selecting the intestinal anastomosis technique was proposed and published in Pediatria Journal
Yu.A. Kozlov, M.N. Mochalov, S.S. Poloyan, P.Zh. Baradieva, D.A. Zvonkov, Ch.B. Ochirov, V.S. Cheremnov, V.M. Kapuller, A.I. Dreglea, A.N. Narkevich. Development of a predictive model for selecting the intestinal anastomosis technique in children with the best predictive power based on ROC-AUC. Pediatria. Journal named after G.N.Speransky. 2022; 10...Read more
The project was supported by RSF
The project "State-of-the-art methods for non-linear crisp and fuzzy dynamic models: theory and applications" was supported by RSF