Welcome to the Machine Learning Group

Machine Learning

Research into novel feature selection techniques and learning algorithms applied to a variety of industrial domains.

Behavioral Intelligence

Research into behavioral aspects of decision making via (evolutionary) game theory and simulations to better understand human behavior.

Big Data

Research into scalable big data solutions for the analysis of complex (e.g. high throughput, high volume, high velocity) data from ICT and medicine

Computational Biology

Research and development into medical and biological questions using machine learning, statistical and modelling approaches

Who are we ?

The Machine Learning Group (MLG), founded in 2004 by G. Bontempi,  is a research unit of the Computer Science Department of the ULB (Université Libre de Bruxelles, Brussels, Belgium), Faculty of Sciences, currently co-headed by Prof. Gianluca Bontempi and Prof. Tom Lenaerts.

MLG targets machine learning and behavioral intelligence research focusing on time series analysis, big data mining, causal inference, network inference, decision-making models and behavioral analysis with applications in data science, medicine, molecular biology, cybersecurity and social dynamics related to cooperation, emotions and others.

Our skills

We harness every aspect of machine learning, artificial intelligence and computer science research to bring breakthrough support in domains such as geographical data mining, fraud detection, big (real)data analysis, intelligent decision-making, behavioral (economic, social and political) studies, complex systems analysis and computational biology/bioinformatics — gene expression and cancer detection, computer-aided medicine and theoretical research.

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Behaviorial intelligence

Experimentally and theoretically analysing human - human and human - AI interactions in order to develop meaningful models.

Feature selection

Reducing the number of features in order to identify those that are most relevant for classification, regression etc.

Supervised and unsupervised learning

learning patterns from labelled and unlabelled data using classification, regression and clustering techniques.

Intelligent decision making

How to adapt to prior decisions and to anticipate future choices of agents in strategic situations.

Computational Biology and Bioinformatics

Developing computational methods and software tools for the analysis and interpretation of biological data.

Game theory

The theory of strategic decision-making in cooperative and non-cooperative situations.

Time Series Analysis

Analysis and multi-step ahead forecasting of multivariate temporal data.

Open source software

Development of publicly available software packages and sharing code analysis through online repositories.

Evolutionary dynamics

Agent learning by social imitation or survival of the fittest.

Our projects

From wireless sensor networks to molecular signatures in human cancers, discover our ongoing and completed projects.

  • All
  • Behavioural Intelligence
  • Big Data
  • Finished project
  • Intelligent Transportation Systems
  • Machine Learning

Our partners

KU Leuven
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49 entries « 10 of 10 »


Domingos, Elias Fernández; Gruji'c, Jelena; Burguillo, Juan J C; Kirchsteiger, Georg; Santos, Francisco C; Lenaerts, Tom

Timing Uncertainty in Collective Risk Dilemmas Encourages Group Reciprocation and Polarization Journal Article

In: iScience, vol. 23, no. 12, 2020, (DOI: 10.1016/j.isci.2020.101752).

Abstract | Links | BibTeX

Gruji'c, Jelena; Lenaerts, Tom

Do people imitate when making decisions? Evidence from a spatial Prisoner's Dilemma experiment: Do people imitate when making decisions Journal Article

In: Royal Society open science, vol. 7, no. 7, 2020, (DOI: 10.1098/rsos.200618).

Abstract | Links | BibTeX

Anciaux, Ma"elle; Demetter, Pieter; Wind, Roland De; Galdon, Maria Gomez; Velde, Sylvie Vande; Lens, Gaspard; Craciun, Ligia; Deleruelle, Amélie; Larsimont, Denis; Lenaerts, Tom; Sclafani, Francesco; Deleporte, Amélie; Donckier, Vincent; Hendlisz, Alain; Vandeputte, Caroline

Infiltrative tumour growth pattern correlates with poor outcome in oesophageal cancer. Journal Article

In: BMJ open gastroenterology, vol. 7, no. 1, 2020, (DOI: 10.1136/bmjgast-2020-000431).

Abstract | Links | BibTeX

Rocha, Luis Mateus; Singh, Vikramjit; Esch, Markus; Lenaerts, Tom; Liljeros, Fredrik; Thorson, Anna

Dynamic contact networks of patients and MRSA spread in hospitals Journal Article

In: Scientific reports, vol. 10, no. 1, 2020, (DOI: 10.1038/s41598-020-66270-9).

Abstract | Links | BibTeX

49 entries « 10 of 10 »

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