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)


Doctoral degree for Mengzi Tang

On September 14, 2021, Mengzi Tang successfully defended her Ph.D. thesis "Machine learning methods for ordinal classification with absolute and relative information" and was awarded the title of Doctor of Bioscience Engineering: Mathematical Modelling. Mengzi was supervised by Bernard De Baets and Raúl Pérez-Fernández of the University of Oviedo, Spain. Her jury included the international expert ‪Pedro Antonio Gutiérrez, professor at the University of Córdoba. The research of Mengzi was supported by the China Scholarship Council.

PhD Mengzi Tang PhD Mengzi Tang

08/08/2021Best Poster Award for Ward Quaghebeur
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Most recent journal publications
Biblio logo(640) Predicting the presence and abundance of bacterial taxa in environmental communities through flow cytometric fingerprinting
J. Heyse, F. Schattenberg, P. Rubbens, S. Müller, W. Waegeman, N. Boon and R. Props
(2021) MSYSTEMS. 6, e00551-21.
Biblio logo(639) A characterization of the classes Umin and Umax of uninorms on a bounded lattice
H.-P. Zhang, M. Wu, Z. Wang, Y. Ouyang and B. De Baets
(2021) FUZZY SETS AND SYSTEMS. 423, 107-121.
Biblio logo(638) Ambient temperature and relative humidity-based drift correction in frequency domain electromagnetics using machine learning
D. Hanssens, E. Van De Vijver, W. Waegeman, M. E. Everett, I. Moffat, A. Sarris and P. De Smedt
(2021) NEAR SURFACE GEOPHYSICS . 19, 541-556.
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