Intelligent Technologies Research Group

Research theme

Research theme "Theoretical and applied aspects of machine learning and mathematical modeling (2019–2021)"
   Physical Sciences (Informatics) 41-T-12, Technological Sciences (Informatics Engineering) 42-E-4

Main goal

Develop and explore models based on machine learning and mathematical modeling for cyber security, anomalous data detection, real-time data classification, prediction, and explanation of results.

 Tasks in 2021:

• Application of machine learning for hyperspectral image analysis.
• GAN networks for phishing URL detection.
• Modeling multi-phase systems.
• Investigation of open computer networks when network load is small.
• Stable modeling in finance engineering.
• Practical aspects of Central limit theorem Borvein algorithm

 Tasks in 2019-2020:

• Application of machine learning in anomalous network data detection
• Adapting heavy tail models to identify abnormalities in security tasks of computer networks
• Modification of classification algorithms for CERN data certification
• Critical region inequalities for Riemann zeta function modules
• Create a recursive algorithm for the recognition of the parameters of the Wiener process monitored with noise
• Create a recursive algorithm for multi-dimensional Dirichlet distribution parameter recognition
• Testing and matching metrics and an agent-based model for measuring the impact of cultural processes on social capital to create a functional simulation prototype
• Get the primary results in the theory of networks with different performance nodes