Download PDF


Age: 30 (born 23/03/1986) Family Status: Married, have kid

Education: Applied Mathematics (Master degree), PhD in Computer Science

Nationality: Russian Languages: Russian (native), English (upper intermediate)

Work History

Sep 2016

Senior Data Analyst

JSC "Visiology"

1. Participation in meetings with business clients, correspondence during project collaboration.
2. Writing specifications for data analysis software development process.
3. Programming and analysis of data using R programming language: data preparation (cleaning, consolidation, aggregation) and analysis, building simulation and predictive mathematical models.
4. Visualization of the revealed relations and regularities, preparation of reports and presentations for management and business clients.
5. Creating advanced analytics dashboards in the field of financial risk modeling using the platform developed by Visiology company.
6. Data analysis team leading.
7. Development and management of the GitHub repository structure for data science projects and.
8. Reverse-engineering of the existing software solution in the field of financial modeling.
9. Creating and maintaining a database of public data sources for use in projects based on advanced analytics or Big Data technologies.

Oct 2013Sep 2016

Head of the Laboratory of Mathematical Psychology and Applied Software

Moscow State University of Psychology and Education, Department of Computer Science
  1. Software development team leading (R, LabVIEW) - see examples of software developed in "Knowledge&Skills" section.
  2. Project management supported by grants of scientific foundations.
  3. Designing and carrying out experimental studies in the field of mathematical and cognitive psychology.
  4. Writing scientifical and conference reports.
  5. Writing articles devoted to the results of scientific research (see full list here -
  6. Creating presentations and posters for conferences and exhibitions.
  7. Participating in domestic and international scientifical and educational exhibitions and conferences.
Sep 2013Sep 2016

Associate Professor of Computer Science

Moscow State University of Psychology and Education, Department of Computer Science

Supervising more than 10 diploma and 20 course projects on specialty "Applied Computer Science" and "Applied Mathematics".

Teaching courses:

  1. Informatics (practical lessons).
  2. Statistical Data Analysis
  3. Machine Learning and Pattern Recognition
  4. Automatisation of Experimental Studies
  5. Psychologial and Еducational Assessment Practicum.
Sep 2008Sep 2016

Statistical Programmer

Moscow State University of Psychology and Education, Department of Computer Science

R and LabVIEW programming for solving statistical data analysis and mathematical modelling tasks in the area of experimental and cognitive psychology.

Developing machine learning applications for educational assessment and psychological diagnostics.

Sep 2008Sep 2006

Laboratory Researcher

Moscow State University of Psychology and Education, Department of Computer Science
  1. Developing of software (LabVIEW) for biomechanical research (stabilography, myography, electroencephalography). 
  2. Implementing a relaxation neural network for recognition of pathological fragments in physiological signals. 
  3. Conducting psychophysiological experiments.
Sep 2005Apr 2006

Assistant Chief Programmer

Alert-M (retail)
  1. Writing SQL-queries (Oracle 9i) and modification of stored procedures.
  2. Creation of Lotus Notes report templates.



PhD in Computer Science (System Analysis)

Institute of System Analysis of Russian Academy of Sciences

Thesis topic: "Methods of identification of hidden factors influencing temporal dynamics of complex socio-economical systems' parameters"


Master degree in Computer Science (with distinction)

Moscow State University of Psychology and Education, Department of Computer Science

Specialisation: "Applied mathematics and programming". 

Knowledge & Skills

Data Analysis Techniques

Classification methods: decision trees, random forests,Bayesian approach, discriminative functions, LDA, logistic regression, multilayer perceptrone (backpropagation), kernel methods, neural networks on radial-basis functions, nearest neighbours (e.g. condensed), model ensembles (bagging, boosting, cascading).

Regression methods: regularised linear regression, polynomial regression, kernel-based linear regression, regression trees.

Dimensionality reduction: LDA, PCA, factor analysis and structural equations modelling, latent trait modelling, wavelet transforms.

Signal processing: Fourier transform, wavelet transforms, denoising, decomposition and forecasting.

Image processing: simple pattern-matching techniques, connected components labeling algorithm, familiarity with complex methods such as Hough transform and Viola-Jones method.

Cluster analysis of data with vector or tensor structure (signals, surfaces).

Feature extraction and selection: filtering and weighting approaches, PCA.

Recommender Systems: basic K-NN based on Pearson correlation; rating matrix factorisation using gradient descent.

Model selection and validation: K-fold cross-validation, bootstrap techniques, Monte-Carlo techniques, learning curves, manual error analysis.

Algorithm performance analysis: R code profiling, time and memory consumption simple analysis techniques. 

R Programming

Solid experience of R programming using RStudio IDE: S3/S4-classes, generic functions, vectorisation techniques, base/lattice/ggplot2 graphical systems, data analysis (dplyr, data.table, reshape, lubridate, tm, mlr, caret, signal, ts, MASS, etc), reports (knitr), interactive dashboards (Shiny), parallel computing (foreach) .

Software developed:

- software for financial risk assessment and control (energy sector) based on the Monte-Carlo method utilizing Geometric Brownian Motion model;

- tools for analysis of large amounts of sensor data (~20 Gb) for chemical production company: time series preprocessing, feature engineering and selection, exploratory analysis, anomaly detection and machine learning (Extremely Randomized Trees techinque for prediction of product quality);

- system for analysis of videooculography data (smoothing, segmentation, clustering, kernel density estimation,  multivariate statistical analysis, complex visualisations);

- utilities for revealing of temporal patterns in psychological testing process by analysis of logged assessment history;

- implementation of Markov chains' parameters optimisation techniques (gradient descent, genetic algorithm, combinatorial methods);

- utilities for calculating images similarity metrics based on 2D-wavelet  transform and linear regression analysis allowing revealing of details in images that influence subjects choice in face discrimination task;

- utilities for estimation of time series of observed state probabilities needed for Markov chains parameters identification;

- software for optimisation of parameters of discriminant functions applied for binary classification tasks;

- software for SMS spam detection using naive Bayes classifier utilizing keywords' probabilities estimates;

- software for polynomial regression fitting.

LabVIEW Programming

Solid experience of LabVIEW programming for developing data analysis products (mostly signal and image processing and Markov chains optimisation).

Software developed:

- mobile application for blind users allowing detection of obstacles utilizing acoustic sonar principle;

- FPGA-software controlling autonomous robot;

- system for biomechanical data acquisition, processing (spectral analysis, wavelet transforms, statistics estimation) and reporting;

- pattern-matching software detecting light-reflective markers in video frames;

- pattern-matching software detecting pathological segments in stabilographical signals utilizing relaxation neural network and wavelet coefficients;

- software for confirmatory factor models validation using Kohonen's self-organising maps and Monte-Carlo approach;

- classification software for estimation of probabilities of aircraft pilots proficiency levels using probabilisitc neural network (similar to kernel-weighted K-nearest neighbour approach);

- implementation of Markov chains' parameters optimisation techniques (gradient descent, genetic algorithm, own combinatorial methods).


Presentation of various projects results at more than 40 conferences (including 5 international European conferences), 15 domestic exhibitions.


Moderate experience (3 years) of giving lectures and practical lessons in the field of Computer Science. More than 10 successfull diploma and 20 course projects.

Statistical Packages Usage: SPSS,Statistica

Experience of using IBM SPSS and StatSoft Statistica for samples comparison, distributions fitting, correlation, regression, factor, LTM and discriminant analysis for educational needs: psycho-educational questionaries standartisation, validation and data mining using small datasets.

Business Processess Analysis

DFD, ER diagrams creation for small software development projects in the area of experimental and cognitive psychology.

MS Excel

Moderate experience of MS Excel for data analytics (probability and statistics, visualisation, Data Analysis and Solver add-ins).


Writing PL-SQL queries and stored procedures for Oracle 9i database. Experience using all relational operations, including JOINs and nested queries.

Reactive Programming (Shiny Framework)

Moderate experience in using Shiny web application framework: developing local application for analysis of videooculography data (see

Big Data Tools

Theoretical background of the Map Reduce computational model, HDFS, Hadoop stack representative developer tools.

C++ Programming (C++ Builder 7)

Elementary experience of C++ programming during Master's degree university program.


Little Matlab/Octave experience: writing basic functions for machine learning systems developed during the Andrew Ng's Machine Learning course at Coursera.

C# Programming (Eclipse)

Elementary experience of C# programming: small modification of GazeTracker system to allow to use Sony PS3Eye Camera with the system  (see



Big Data Modeling and Management Systems

University of California, San Diego

Introduction to Big Data

University of California, San Diego

No certificate provided


Machine Learning (Andrew Ng's)

Stanford University

No certificate provided

Learning from Data by Yaser Abu-Mostafa

California Institute of Technology

No certificate provided


Exploratory Data Analysis

John Hopkins Bloomberg School of Public Health @ Coursera

Getting and Cleaning Data

John Hopkins Bloomberg School of Public Health @ Coursera

R Programming

John Hopkins Bloomberg School of Public Health @ Coursera

Reproducible Research

John Hopkins Bloomberg School of Public Health @ Coursera

Statistical Inference

The Data Scientist’s Toolbox

John Hopkins Bloomberg School of Public Health @ Coursera


Computing for Data Analysis

John Hopkins Bloomberg School of Public Health @ Coursera

Personal Qualities

- Abstract thinking, systematic inventive thinking, critical mind

- Aspired to solve problems, not to avoid them

- Responsible, punctual, efficient, polite

- Leadership skills, teamwork skills

- Adaptable, self-paced learner, open-minded