Selected Publications

Opracowanie stanowi podsumowanie wyników projektu badawczego realizowanego w Zakładzie Zdrowia Dzieci i Młodzieży Instytutu Matki i Dziecka w Warszawie w latach 2014-2017 w ramach umowy z Narodowym Centrum Nauki (nr 09/B/HS6/03438) w konkursie OPUS 5. Projekt zatytułowany był: Środowisko fzyczne i społeczne oraz jakość funkcjonowania szkoły a zdrowie subiektywne i zachowania zdrowotne nastolatków – zastosowanie modeli strukturalnych i ścieżkowych szacowanych na danych o strukturze hierarchicznej.
Instytut Matki i Dziecka, Warszawa 2017

In recent years, there has been increased interest in methods for gender prediction based on first names that employ various open data sources. These methods have applications from bibliometric studies to customizing commercial offers for web users. Analysis of gender disparities in science based on such methods are published in the most prestigious journals, although they could be improved by choosing the most suited prediction method with optimal parameters and performing validation studies using the best data source for a given purpose.
In The R Journal

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W sobotę (24.06) odbyło się na WSIiZ insprujące seminarium z udziałem on-line prof. P.Zimbardo. Philip Zimbardo był w 1971 roku liderem sławnego Stanfordzkiego Eksperymentu Więziennego i świadkiem-ekspertem w sprawie więzienia Abu Ghraib. Autor wpływowych książek: The Time Paradox: The New Psychology of Time That Will Change Your Life i The Lucifer Effect: Understanding How Good People Turn Evil. Warto zapoznać się z projektem Profesora Zimbardo: Heroic Imagination Project.


Here is a selection of my Data Science and Programming skills and tools that turned out to be helpful in my work and I believe are important for any Data Scientist as well. The last update of this post was done: 2017-07-21. Data Science Skills Data Manipulation Efficient data manipulation in R; dplyr, data.table, reshape2. Working with dates and time-series; lubridate, xts. Reproducible Analyses RStudio IDE, Markdown, LaTeX;


This post is an annotated bibliography of helpful resources for programming and doing Data Science in R. I will try to expand this list and add some short recommendations in the future. The last update of this post was done: 2017-07-21. Books (on-line & printed) Hadley Wickham, Advanced R The book is designed primarily for R users who want to improve their programming skills and understanding of the language. It should also be useful for programmers coming to R from other languages, as it explains some of R’s quirks and shows how some parts that seem horrible do have a positive side.


This new homepage is a static website generated in R (!) with the help of brilliant blogdown package by Yihui Xie. Hugo is the site engine and it also uses amazing Academic theme.

More about the blogdown R package you can find here:

Some additional usefull posts:


UPDATE: The online static version of the presentation is available here: Thank you for all the feedback! In two days, from 12 to 14 October, 2016 in Poznan (Poland) will take place the conference “eRum 2016: european R users meeting“. I will give a talk about new R package: LimeRick. LimeRick enables close connection between two important open-source projects: R and LimeSurvey. LimeSurvey is the most advanced open-source system for on-line survey and Computer Aided Web Interviewing (CAWI) and together with R they offer advanced ecosystem for gathering and analyzing declarative data.


Research & Software


  • Closed Open Data

    Barriers & bad practices in accessing Open Data. Case study of Poland.

  • limeRick

    The bridge between LimeSurvey and R.

  • genderizeR

    The R package for gender prediction based on first names.

  • RRUG

    Resovia R User Group

Teaching & Training

Graduate, Postgraduate & PhD Level

  • Statistics
  • Inferential Statistics
  • Analysis and Visualisation of Economic Data
  • Introduction to R (PhD level workshop)

Hire me!

What can I do for you?

  • Collaboration in non-profit & commercial research projects
    • reproducible data analysis
    • machine learning & statistical analysis
    • scripting for on-line surveys data collection
    • Computer-Aided Web Interviewing (CAWI)
    • interactive web reporting of research data
    • co-authoring research papers
  • R packages development
    • GitHub & CRAN deployment
  • Data Producs development
    • reactive programming in R & Shiny
    • prototyping and expanding Shiny application
  • Trainings in R programming and data analysis
  • Methodological & Analytical Consultations

Feel free to send me an e-mail if you have any questions!


See also


Open Data Institute ODI Research Data Alliance