KERMIT -- Research Unit Knowledge-based Systems

Date	Title
18/08/2014	2015 IEEE CIS Outstanding TFS Paper Award
27/08/2012	Best Paper Award for Willem Waegeman
17/08/2012	Second Winner Award for Willem Waegeman

Name	Title	Date
N. Dewolf	A comparative study of conformal prediction methods for valid uncertainty quantification in machine learning	25/04/2024
D. Iliadis	Automated multi-target prediction with two-branch neural networks	17/11/2023
T. Mortier	Efficient algorithms for set-valued prediction in classification	23/06/2023
M. Gasparyan	Model reduction and parameter estimation for kinetic models of biochemical reaction networks	19/01/2023
F. Mey	Integration of synthetic biology, systems biology and machine learning for the production of chitooligosaccharides in Escherichia coli	18/01/2023
J. Clauwaert	Deep learning techniques for genome processing and annotation tasks in prokaryotes	24/09/2020
P. Rubbens	Machine learning approaches for microbial flow cytometry at the single-cell and community level	24/09/2019
C. Papagiannopoulou	A data-guided insight into global climate-vegetation dynamics	05/10/2018
M. Stock	Exact and efficient algorithms for pairwise learning	21/04/2017

MSc Students

Name	Title	Date
N. Tourne	Two-branch neural networks for predicting protein-DNA interaction	2022 - 2023
J.-H. Nowé	Countering illegal timbering by using multimodal machine learning	2022 - 2023
Y. Van Laere	Detection of 5mC modification in Nanopore sequencing data using deep learning	2021 - 2022
E. Lorrez	Quantifying the environmental controls on African tropical forest dynamics through using a Granger causality framework	2020 - 2021
K. Zhang	Drug-target interaction prediction using multi-target prediction methods	2020 - 2021
L. Theunissen	A comparison of flat and hierarchical classification for automatic annotation of single-cell transcriptomics data	2020 - 2021
T. Willaert	Improving classification by rejection of high epistemic uncertainty points	2020 - 2021
L. Pollaris	Protein secondary structure prediction using transformer networks	2019 - 2020
B. De Saedeleer	Combatting illegal timber trade using chemical fingerprints: the power of mathematics and mass spectrometry	2019 - 2020
B. Verfaillie	Pattern recognition in raman spectroscopy data for a faster labelling of subjects in multiple domains	2019 - 2020
L. Davey	Using artificial neural networks to uncover features in promoter sequences responsible for nonorthogonality in E. Coli	2019 - 2020
G. Tjon	Automative drinking water monitoring using flow cytometry data	2019 - 2020
S. Top	Vertical farming of lettuce: the influence of rhizosphere bacteria and substrates	2018 - 2019
K. D'haeyer	Towards a data-driven identification of the microbial "Rammanome"	2018 - 2019
G. De Clercq	Deep learning for classification of DNA functional sequences	2018 - 2019
N. Goeders	Fight the illegal wood trade through chemical fingerprints : The power of mathematics and mass spectrometry	2018 - 2019
B. De Clercq	Forecasting tidal surge in the Lower Sea Scheldt using machine learning techniques	2018 - 2019
M. Van Haeverbeke	Detection of m6a modifications in native RNA using Oxford Nanopore Technology	2018 - 2019
M. Misonne	Prediction of RNA polymerase-DNA interactions in Escherichia Coli	2017 - 2018
R. Ingels	Understanding vegetation anomalies with machine learning methods	2017 - 2018
A. De Graeve	Detecting climate drivers for vegetation extremes	2017 - 2018
T. Vanlerberghe	Hierarchical multi-label classification of food products	2017 - 2018
T. Mortier	Modeling of climate-vegetation dynamics using machine learning techniques in a non-linear Granger causality framework	2016 - 2017
X. Yin	Discovering relationships in climate-vegetation dynamics using dynamic feature selection techniques	2016 - 2017
D. Schaumont	Een integratieve benadering gebaseerd op random forest voor de verbeterde predictie van exon-intron juncties	2016 - 2017
C. Zhang	Visualization and unsupervised learning of flow cytometry data for bacterial identication	2016 - 2017
S. Decubber	Spatiotemporal optimization of Granger causality methods for climate change attribution	2016 - 2017
J. Heyse	Development and application of single-cell analysis tools for the study of sympatric bacterial populations	2016 - 2017
L. Bodyn	Exploration of deep autoencoders for collaborative filtering on cooking recipes	2016 - 2017
L. Tilleman	In silico engineering van cytochroom P450 via machine learning technieken	2015 - 2016
F. Ramon	A data-driven analysis of ingredients in cooking recipes	2015 - 2016
W.K. Tsang	Assessing pathogen invasion based on community evenness and metabolic similarity	2014 - 2015
J. De Reu	Analyse van voorspellingsmodellen voor aardappelziekten en hun toepasbaarheid in Vlaanderen	2014 - 2015
M. De Clercq	Prediction of ingredient combinations using machine learning techniques	2013 - 2014
A. De Paepe	The prediction of interaction between mRNA and miRNA using machine learning techniques	2012 - 2013
M. Stock	Learning pairwise relations in bioinformatics: three case studies	2011 - 2012
J. Vandepitte	Voorspellen van Fusarium spp. aanwezigheid en DON concentraties in wintertarwe met machine learning technieken	2009 - 2010

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