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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)

News

Steff Taelman nominated for the EOS prize

On the 21st of December, 2019, Steff Taelman’s dissertation on "A dual computational approach to map domain architecture in phage lytic proteins " was nominated for the EOS prize for best thesis in the exact sciences. This dissertation - a combined effort between KERMIT, BioBix and the Laboratory of Applied Biotechnology (supervised by M. Stock, Y. Briers, W. Van Criekinge and B. Criel) - used a combination of bioinformatics and machine learning to uncover design rules in bactericidal proteins encoded by viruses. Read Steff’s interview here and read his popular science article here.

EOS prize Steff Taelman EOS prize Steff Certificate

01/12/2019Bernard De Baets appointed Professor Extraordinarius at UNISA
All KERMIT news

Publications

Most recent journal publications
(556) On the construction of uninorms by paving
W. Zong, Y. Su, H.-W. Liu and B. De Baets
(2020) INTERNAT. J. APPROXIMATE REASONING. 118, 96-111.
Biblio logo(555) Scalable large-margin distance metric learning using stochastic gradient descent
B. Nguyen, C. Morell and B. De Baets
(2020) IEEE TRANSACTIONS ON CYBERNETICS. 50, 1072-1083.
(554) Identification of Cellular Automata based on incomplete observations with bounded time gaps
W. Bolt, J.M. Baetens and B. De Baets
(2020) IEEE TRANSACTIONS ON CYBERNETICS. 50, 971-984.
All KERMIT publications