Department
AS

Head — Irina V. Rozora - Prof., Doctor of Physical and Mathematical Sciences
Faculty of Computer Science and Cybernetics, Department of Applied Statistics
The Department specializes in fundamental research in probabilistic and statistical methods, stochastic analysis and modeling, and modern statistical theory. It also focuses on the mathematical foundations of data science, machine learning, and financial and actuarial mathematics.
The Department provides training for Bachelor's students in the Systems Analysis program, Master's students in the Social Data Analysis and Systems and Methods of Decision Making programs, and PhD students in the Systems Analysis doctoral program.
Probability Theory, Mathematical Statistics, Data Analysis, Actuarial Mathematics, Queueing Networks, Mathematical Methods for Analyzing, Complex Systems, Data Mining, Open Sources and Web Scraping, Mathematical Methods for Insurance and Pension, Schemes Time Series: Analysis and Forecasting, Spatial Data Analysis, Bayesian Networks, Machine Learning, Algorithms for Classification Problems and more

Department of Applied Statistics

8

Teachers

The Department has 8 full-time faculty members: 1 Professor, 4 Associate Professors, and 3 Assistant Lecturers. Of these, 1 holds a Doctor of Sciences

35

Courses

Department faculty teach 35 core and elective courses.

48

Years

The Department of Applied Statistics was established on June 7, 1978

Staff:

Full name: Office Research interests
Head of the Department, Professor Irina V. Rozora 709 property investigation of stochastic processes and fields, modelling of random processes with given accuracy and reliability in various Banach spaces, actuarial mathematics
Prof. Pavlo S. Knopov 709 statistical decision theory, methods of stochastic optimization, theory of optimal control of stochastic systems
Prof. Natalia V. Semenova 709 development and research models and methods of discrete optimization, as well as problems with ambiguous data set, stability analysis of vector discrete optimization problems.
Assoc. Prof. Alexander S. Slabospitsky 706 б estimation theory, data analysis, applied statistics, regression analysis, analysis of variance, correlation analysis, system identification theory, parameter/state estimation of technical objects, recurrent algorithms of system identification, set membership estimation, real-time data processing, system modelling, asymptotic analysis of estimation and identification algorithms, software for analysis and processing of data, computer networks, Internet-technologies
Assoc. Prof. Hanna V. Livinska 709 Stochastic processes, queueing systems and networks, asymptotic analysis of stochastic systems, multivariate statistical analysis; machine learning algorithms and methods; time series.
Assoc. Prof. Michael M. Sharapov 706 б limiting theorems for estimates of parameters of random processes and fields with long memory, modeling of random processes and fields with long memory, random walks on graphs, combinatorial solutions of linear programming task, computer realizations of statistical algorithms
Assoc. Prof. Vadym D. Ponomarov 709 random processes, optimal control of stochastic systems, modern programming technologies, evaluation theory
Assist. Prof. Igor A. Makushenko 709 investigation of stochastic processes of queueing theory, asymptotic analyses of compound stochastic systems, statistical prediction methods
Assist. Prof. Volodymyr I. Morenets 709 Games with a fuzzy set of agents, machine learning, open sources and web scraping, sample surveys, data mining.
Assist. Prof. Andrii V. Urazovskyi 607 Багатовимірні часові ряди, моделювання стохастичних систем, непараметричні підходи оперативної діагностики точок переходу для моніторингу складних систем.
Assist. Prof. Viktor V. Semenov 709 development and research of models and methods of discrete optimization and solvability of vector discrete optimization problems.