Marek Gagolewski

Marek Gagolewski, PhD, Dr habil.

ORCID ORCID=0000-0003-0637-6028

Senior Lecturer in Applied Artificial Intelligence
School of Information Technology, Deakin University
Melbourne Burwood Campus, Room T2.20-WS12
221 Burwood Hwy, Burwood, VIC 3125, Australia
Emails (pick one – and only one):
marekgagolewski·com (main)
M.Gagolewskideakin·edu·au (academic – Deakin University)
M.Gagolewskimini·pw·edu·pl (academic – Warsaw University of Technology)
See also:  ResearchGate Google Scholar
My academic CV


Researcher in Machine Learning, Applied Artificial Intelligence, Data Fusion and Statistical Modelling

  • Author of the fast&robust Genie clustering algorithm CRAN package genie PyPI package genieclust

Machine Learning, Data Analysis and Scientific Computing Software Developer (Python, C, C++, R, etc.)

Data Science, Machine Learning, Python, R and C++ Tutor & Trainer

Recent News

2019-11-14 new paper

Robust fitting for the Sugeno integral with respect to general fuzzy measures

The editor of Information Sciences have just let us know that a paper by Gleb Beliakov, Simon James and me will be published in this outlet. Read more…


Deakin University

On 23rd of September 2019 I commence as a Senior Lecturer in Applied Artificial Intelligence at Deakin University in Melbourne-Burwood, Australia (Australian senior lecturer is supposed to be equivalent to an associate professor in the US).

2019-09-10 new paper

Constrained Ordered Weighted averaging aggregation with multiple comonotone constraints

Lucian Coroianu, Robert Fullér, Simon James and I got a paper accepted in the Fuzzy Sets and Systems outlet. Abstract below. Read more…

2019-06-17 new PhD

Jan Lasek's PhD defence

My PhD student, Jan Lasek, has successfully defended his doctoral thesis, New data-driven rating systems for association football. :)

2019-06-08 new paper

Aggregation on ordinal scales with the Sugeno integral for biomedical applications

Gleb Beliakov, Simon James and I got another paper accepted for publication in Information Sciences. This time we re-write a learning-to-aggregate problem based on the Sugeno integral in a difference-of-convex objective setting. The derived tool is particularly useful when working with ordinal data. Read more…

Browse all news