Marek Gagolewski

Dr habil. Marek Gagolewski

(Pronounced like Mark Gaggle-Eve-Ski) 🙃

🏷 Senior Lecturer in Applied Artificial Intelligence
🏛 School of Information Technology, Deakin University
📪 Melbourne-Burwood Campus, Room T2.20, 221 Burwood Hwy, Burwood, VIC 3125, Australia
Emails (pick one – and only one):
marek🔶gagolewski🔹com (main)
m🔹gagolewski🔶deakin🔹edu🔹au (academic)
See also:  • GitHubStackOverflowVitæ ORCID=0000-0003-0637-6028



Researcher in the Science of Data (with particular emphasis on modelling of complex phenomena and developing of usable, general purpose algorithms)

  • Research interests: machine learning; data fusion, aggregation, and clustering; computational statistics; mathematical modelling in informetrics, sports analytics, and science of science – amongst others
  • Author or co-author of 79 publications (see featured papers), including 37 journal papers in outlets such as Proceedings of the National Academy of Sciences (PNAS), Information Fusion, International Journal of Forecasting, Statistical Modelling, R Journal, Information Sciences, Knowledge-Based Systems, IEEE Transactions on Fuzzy Systems, and Journal of Informetrics
  • Eligible Principal Supervisor at PhD level (principal supervisor of 3 PhD and 11 MSc by research students from commencement through to successful completion) – feel welcome to contact me if you have any interesting research ideas (and essential capabilities such as programming skills (Python, R, C/C++, etc.), data wrangling, matrix algebra, probability and statistics, and optimisation)

Free (Libre) and Open Source Data Analysis Software Developer


Data Science, Machine Learning, and Statistical Computing Tutor & Trainer

Recent News

2021-08-26 new paper

T-norms or t-conorms? How to aggregate similarity degrees for plagiarism detection

A new paper by Maciek Bartoszuk and me is to appear in Knowledge-Based Systems (doi:10.1016/j.knosys.2021.107427). Read more…

2021-07-29 software

stringx: Drop-in replacements for base R string functions powered by stringi

English is the native language for only 5% of the World population. Also, only 17% of us can understand this text. Moreover, the Latin alphabet is the main one for merely 36% of the total. The early computer era, now a very long time ago, was dominated by the US. Due to the proliferation of the internet, smartphones, social media, and other technologies and communication platforms, this is no longer the case. The stringx package replaces base R string functions (such as grep(), tolower(), and sprintf()) with ones that fully support the Unicode standards related to natural language processing, fixes some long-standing inconsistencies, and introduces some new, useful features. Thanks to ICU (International Components for Unicode) and stringi, they are fast, reliable, and portable across different platforms. Now available from CRAN.

2021-07-14 software

stringi 1.7.2

Another major update of stringi brings a rewritten version of stri_sprintf, support for custom rule-based transliteration, extraction of named regex capture groups, and many other enhancements. Read more…

2021-06-17 software

realtest 0.2.1 on CRAN

An update to realtest is now available. Read more…

2021-06-04 software

realtest: When Expectations Meet Reality: Realistic Unit Testing in R

realtest is a framework for unit testing for realistic minimalists, where we distinguish between expected, acceptable, current, fallback, ideal, or regressive behaviour. It can also be used for monitoring other software projects for changes. Now available on CRAN.

2021-05-27 new paper

Paper on the genieclust Python+R package

genieclust: Fast and robust hierarchical clustering was accepted for publication in SoftwareX (doi:10.1016/j.softx.2021.100722). Read more…

2021-05-17 software

stringi 1.6.2

stringi is now shipped with ICU4C 69.1 which supports Unicode 13.0 and CLDR 39. Read more…

2021-04-22 software

genieclust 1.0.0

A maintenance release of the Python and R package genieclust for fast and robust hierarchical clustering with noise point detection is now available on PyPI and CRAN.

Browse all news