Expertise Summary   (Prof. I.V. Semushin)  
  • Strong foundations in theoretical computer science, applied mathematics, and mathematical information technology coupled with the knowledge in electrical engineering and electronics
  • Extensive practical work in system modeling, analysis and design
  Knowledge and experience in MIT - Mathematical Information Technology  

MIT in Decision Support Systems:
  • Detection of abrupt changes in dynamical system models
  • Linear and nonlinear programming
  • Sequential methods in statistical hypotheses testing and pattern recognition

MIT in Data Processing and Control Systems:
  • Ordinary and total least squares
  • Digital signal spectra analysis
  • Discrete time multi-input multi-output control systems
  • Stochastic optimal linear estimation and control
  • Adaptive filtering and control systems
  • Robust methods of estimation and control

MIT in system modeling and analysis:
  • Regression, pseudoinverse and recurrent estimation
  • Stochastic system models estimation
  • Combined navigation systems: error budget analysis and component optimization

MIT in computation:
  • Traditional linear algebra computation methods
  • Modern linear algebra computation methods: factorization, orthogonalization, and parallelization
  Knowledge and experience in other fields  

Computer Science:
  • Discrete Mathematics
  • Computer engineering: computer organization, algorithms, and digital automata design

University Education:
  • Curricula design in applied mathematics and computer-based education
  • Computed-aided education methods