Summary

Age: 29 (born 23/03/1986)

Education: applied mathematician (Master degree), PhD in Computer Science

Languages: Russian (native), English (intermediate)

Nationality: Russian

Relocation: Yes

Work History

Work History
Oct 2013 - Present

Head of the Laboratory of Mathematical Psychology and Applied Software

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

Software development team lead, project management supported by grants of scientific foundations, designing and carrying out experimental studies in the field of mathematical and cognitive psychology, writing articles, scientifical and conference reports, creating presentations and posters for conferences and exhibitions.

Sep 2013 - Present

Associate Professor of Computer Science

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

Courses Taught: 1. Informatics 2. Statistical Data Analysis 3. Machine Learning and Pattern Recognition 4. Automatisation of Experimental Studies 5. Psychologial and Еducational Assessment Practicum.

Sep 2008 - Present

Statistical Programmer

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

R and LabVIEW programming for solving data analysis and mathematical modelling tasks in the fields of experimental and cognitive psychology and adaptive psycho-educational assessment.

Sep 2008 - Sep 2006

Laboratory Researcher

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

Development of software (LabVIEW) for biomechanical research (stabilography, myography). Implementation of recognition of pathological fragments in
physiological signals using relaxation neural network. Conduct psychophysiological experiments.

Sep 2005 - Apr 2006

Assistant Chief Programmer

Alert-M (retail)

Writing SQL-queries (Oracle 9i) and modification of stored procedures, creation of Lotus Notes report templates.

Education

Education
2008 - 2011

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"

2003 - 2008

Master degree in Computer Science (with distinction)

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

Specialisation: "Applied mathematics and programming". 

Skills

Skills

Data Analysis Techniques

Classification methods: decision trees, 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, digital filters, denoising, decomposition and forecasting (Holt-Winters model).

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: S4-classes, generic functions, vectorisation techniques, base/lattice/ggplot2 graphical systems,  main data analysis libraries knowledge (caret/signal/ts/MASS, etc).

Software developed:

- freeware 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, own 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

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

Teaching

Moderate experience (3 years) of giving lectures and practical lessons in the field of Computer Science. More than 10 successfull diploma and 30 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 (basic probability and statistics, visualisation, Data Analysis and Solver add-ins).

SQL/PL-SQL

Writing PL-SQL queries and stored procedures for Oracle 9i database.

Reactive Programming

Familiarity with reactive programming concepts implemented in Shiny SDK.

Shiny Framework

Moderate experience in using Shiny web application framework: developing local application for analysis of videooculography data (see http://github.com/PMarmalyuk/EyeTrackingProject).

C++ Programming (C++ Builder 7)

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

Matlab/Octave

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 http://sourceforge.net/projects/gazetrackinglib/files/gazetrackinglib/).

Certifications

Certifications
2015 - 2015

Machine Learning (Andrew Ng's)

Stanford University

No certificate provided

2014 - 2014

Exploratory Data Analysis

John Hopkins Bloomberg School of Public Health @ Coursera

https://www.coursera.org/account/accomplishments/verify/Q263WYNW8N

2014 - 2014

Getting and Cleaning Data

John Hopkins Bloomberg School of Public Health @ Coursera
2014 - 2014

R Programming

John Hopkins Bloomberg School of Public Health @ Coursera

https://www.coursera.org/account/accomplishments/verify/C39WSC8VYL

2014 - 2014

Reproducible Research

John Hopkins Bloomberg School of Public Health @ Coursera

https://www.coursera.org/account/accomplishments/verify/7LTKNDQT9W

2014 - 2014

Statistical Inference

https://www.coursera.org/account/accomplishments/verify/YUDZQVKAXK

2014 - 2014

The Data Scientist’s Toolbox

John Hopkins Bloomberg School of Public Health @ Coursera

https://www.coursera.org/account/accomplishments/verify/AZ2HC7JW6A

2013 - 2013

Computing for Data Analysis

John Hopkins Bloomberg School of Public Health @ Coursera