Mission statement

The research unit KERMIT (Knowledge-based Systems) adopts a holistic view on mathematical and computational modelling, acknowledging the needs of our modern information society with a particular focus on the applied biological sciences. It strives to keep a unique balance between theoretical developments and practical applications, a strategy that has proven particularly successful, regarding the output, visibility and recognitions of the team. It plays a pioneering role by promoting existing as well as developing new methods in a broad range of disciplines shown below.

Methodological expertise

KERMIT started out in 2000 with two men and a dog as a team in fuzzy set theory and preference modelling, and quickly expanded into the fields of artificial/computational intelligence and operations research. Over the years, it has evolved into a holistic team covering the entire data-to-decision pipeline. It provides methodological expertise in the following areas:

  • image processing and computer vision (e.g. mathematical morphology, filters)
  • knowledge-based systems (e.g. bioportals, ontologies)
  • dynamical modelling (e.g. differential equations, cellular automata, individual-based models)
  • data science and machine learning (e.g. time series prediction, structured prediction, deep learning, big data)
  • management of imprecision and uncertainty (e.g. probability, possibility and fuzzy set theory; stochastic modelling, theory of copulas)
  • optimization and operations research (e.g. preference modelling, multi-criteria decision making)


Marc Sader, first Lebanese PhD graduate of KERMIT

On August 29, 2019, Marc Sader defended his Ph.D. thesis "Combining absolute and relative evaluations for determining sensory food quality: analysis and prediction" and was awarded the title of Doctor of Applied Biological Sciences. Marc was supervised by Bernard De Baets. His jury included the international expert José​ Luis García Lapresta.

PhD Marc Sader PhD Marc Sader

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Most recent journal publications
Biblio logo(534) Real-time prediction of influenza outbreaks in Belgium
G.H.B. Miranda, J.M. Baetens, N. Bossuyt, O.M. Bruno and B. De Baets
(2019) EPIDEMICS. 28, 100341.
Biblio logo(533) Analysis of spatio-temporal fungal growth dynamics under different environmental conditions
L. De Ligne, G. Vidal-Diez de Ulzurrun, J.M. Baetens, J. Van Den Bulcke, J. Van Acker and B. De Baets
(2019) IMA FUNGUS. 10, 7.
Biblio logo(532) All binary number-conserving cellular automata based on adjacent cells are intrinsically one-dimensional
B. Wolnik and B. De Baets
(2019) PHYSICAL REVIEW E. 100, 022126.
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