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 recognition 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)


Research of Steff Taelman on the cover of "Scriptiekrant"

Given the omnipresence of viruses in the media, especially the covid-19 virus, on the 10th of July, 2020, an online article about Steff Taelman’s dissertation on the use of machine learning to design protein recombinations as targeted enzybiotics was published in the summer edition of the “ScriptieKrant". This dissertation was a combined effort between KERMIT, BioBix and the laboratory of Applied Biotechnology (supervised by M. Stock, Y. Briers, W. Van Criekinge and B. Criel). You can read the article here.

All KERMIT news


Most recent journal publications
Biblio logo(590) Perspective: Towards automated tracking of content and evidence appraisal of nutrition research
C. Yang, D. Hawwash, B. De Baets, J. Bouwman and C. Lachat
(2020) ADVANCES IN NUTRITION. 11, 1079-1088.
(589) Efficient enumeration of three-state two-dimensional number-conserving cellular automata
A. Dzedzej, B. Wolnik, A. Nenca, J.M. Baetens and B. De Baets
Biblio logo(588) Quantifying and reducing epistemic uncertainty of passive acoustic telemetry data from longitudinal aquatic systems
S. Bruneel, P. Verhelst, J. Reubens, J.M. Baetens, J. Coeck, T. Moens and P. Goethals
(2020) ECOLOGICAL INFORMATICS. 59, 101133.
All KERMIT publications