Skip to main content
Welcome to Machine Learning, Computer Vision, and Dynamic Systems Group

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

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

Learn about us!

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

We're doing researches in

Machine Learning

Differential and Integral models

Numerical analysis

Inverse problems

Latest news

Paper accepted for ICEMS 2021!
The paper «A Study On The Effect of Energy Storage System Optimal Operation With Distributed Generators On System Reliability» was accepted for the International Conference on Electrical Machines and Systems ( ICEMS 2021, Korea).
Paper accepted for IEEE Transactions on Artificial Intelligence
The paper by Q. Tao, L. Fang, D. Yang, and D. Sidorov «Bidirectional Gated Recurrent Unit-Based Lower Upper Bound Estimation Method for Wind Power Interval Prediction» was accepted for publication by IEEE Transactions on Artificial Intelligence. Congrats!
Paper accepted!
The paper by Noeiaghdam S. and Sidorov D. Valid Implementation of the Fractional Order Model of Energy Supply-Demand System published in Mathematical Optimisation Theory and Operations Research: Recent Trends. MOTOR 2021. Communications in Computer and Information Science, vol 1476. Springer, Cham. https://doi.org/10.1007/978-3-030-86433-0_34 Congr...Read more
Manuscript accepted for ICEMS 2021!
The manuscript «The optimal operation of energy storage systems with distributed generators by using the data-based prediction method» by Beopsoo Kim, Nikita Rusetskii, Konstantin Shusterzon, Denis Sidorov, and Insu Kim, was accepted for Intl. Conference on Electrical Machines and Systems, HICO, Korea. Congrats!