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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

Doctoral degree for Gang Wang

On November 19, 2019, Gang Wang successfully defended his Ph.D. thesis "Automated image analysis using Gaussian-based convolutional kernels and deep convolutional networks". He was the first recipient of the title of Doctor of Bioscience Engineering: Mathematical Modelling at the Faculty of Bioscience Engineering of Ghent University. Gang was supervised by Bernard De Baets. His jury included the international expert Pedro Melo-Pinto, professor at the Universidade de Trás-os-Montes e Alto Douro, Vila Real, Portugal. The research of Gang was supported by the China Scholarship Council.

PhD Gang Wang PhD Gang Wang PhD Gang Wang

08/11/2019Best Thesis Abstract Nomination for Gang Wang
31/10/2019Adam Dzedzej, first PhD graduate at the University of Gdańsk
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Publications

Most recent journal publications
Biblio logo(545) A statistical approach to the identification of Diploid Cellular Automata based on incomplete observations
W. Bolt, A. Bolt, B. Wolnik, J.M. Baetens and B. De Baets
(2019) BIOSYSTEMS. 186, 103976.
Biblio logo(544) Randomized lasso links microbial taxa with aquatic functional groups inferred from flow cytometry
P. Rubbens, M. Schmidt, R. Props, B. Biddanda, N. Boon, W. Waegeman and V. Denef
(2019) MSYSTEMS. 4, 00093-19.
Biblio logo(543) A protocol for automated timber species identification using metabolome profiling
V. Deklerck, T. Mortier, N. Goeders, RB. Cody, W. Waegeman, E. Espinoza, J. Van Acker, J. Van den Bulcke and H. Beeckman
(2019) WOOD SCIENCE AND TECHNOLOGY. 53, 953-965.
All KERMIT publications