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Researcher
Willem Waegeman
- Keywords:Machine Learning, Data Science
- Disciplines:Applied mathematics in specific fields, Other computer engineering, information technology and mathematical engineering not elsewhere classified, Modelling and simulation, Systems theory, modelling and identification, Bio-informatics
Affiliations
- Department of Data analysis and mathematical modelling (Department)
Member
From1 Jan 2018 → Today - Department of Mathematical Modelling, Statistics and Bio-informatics (Department)
Member
From1 Dec 2008 → 31 Dec 2017 - Department of Electromechanical, Systems and Metal Engineering (Department)
Member
From16 Aug 2004 → 30 Nov 2008
Projects
1 - 10 of 11
- Uncertainty in machine learningFrom1 Jan 2024 → TodayFunding: BOF - projects
- New-to-nature Biological Sensors: Unlocking the full potential of biological sensors beyond natureFrom1 Oct 2022 → TodayFunding: FWO senior postdoctoral fellowship
- Novel neural networks for single-cell sequencing technologiesFrom1 Nov 2021 → TodayFunding: FWO fellowships
- Retracing the steps of enzyme evolution: an exploration of ancestral sequence spaceFrom1 Oct 2020 → 30 Sep 2023Funding: FWO junior postdoctoral fellowship
- Identification of adaptive mechanisms leading to reduced antibiotic susceptibility in bacterial biofilms using experimental evolution and machine learning approachesFrom1 Jan 2020 → TodayFunding: BOF - projects
- Interlocking synthetic biology, systems biology and artificial intelligence to develop a more efficient metabolic engineering workflow: a highly efficient biotechnological production platform for monoclonal chitooligosaccharides.From1 Jan 2019 → 31 Dec 2022Funding: FWO Strategic Basic Research Grant
- Microbial resource management of aquaculture ecosystems to prevent pathogen invasionFrom1 Jan 2018 → 31 Dec 2021Funding: FWO Strategic Basic Research Grant
- Synthetic biology and artificial intelligence, mutual learning to advance together and jointly drive industrial biotechnology - accelerating knowledge discovery and strain engineeringFrom1 Oct 2016 → 31 Jul 2021Funding: BOF - Doctoral projects
- Nieuwe applicaties in informatiebevraging, beeldverwerking en bio-informatica hebben geleid tot de ontwikkeling van nieuwe machine learning methoden om meerdere targets tegelijkertijd te voorspellen. Recent werden tal van nieuwe methoden ontwikkeld in verFrom1 Feb 2015 → 30 Nov 2019Funding: BOF - Doctoral projects
- Past climate extremes and their impact on the terrestrial carbon cycleFrom1 Oct 2014 → 30 Mar 2019Funding: STEREO II (Support to the Exploitation and Research in Earth Observation data)
Publications
1 - 10 of 162
- A framework for tracing timber following the Ukraine invasion(2024)
Authors: Thomas Mortier, Jakub Truszkowski, Marigold Norman, Markus Boner, Bogdan Buliga, Caspar Chater, Henry Jennings, Jade Saunders, Rosie Sibley, Alexandre Antonelli, et al.
Pages: 390 - 401 - Uncertainty-aware single-cell annotation with a hierarchical reject option(2024)
Authors: Lauren Theunissen, Thomas Mortier, Yvan Saeys, Willem Waegeman
- A comparison of embedding aggregation strategies in drug-target interaction prediction(2024)
Authors: Dimitrios Iliadis, Bernard De Baets, Tapio Pahikkala, Willem Waegeman
- Hyperparameter optimization of two-branch neural networks in multi-target prediction(2024)
Authors: Dimitrios Iliadis, Marcel Wever, Bernard De Baets, Willem Waegeman
- A comparative study of conformal prediction methods for valid uncertainty quantification in machine learning(2024)
Authors: Nicolas Dewolf, Bernard De Baets, Willem Waegeman
- Out-of-sample R2 : estimation and inference(2024)
Authors: Stijn Hawinkel, Willem Waegeman, Steven Maere
Pages: 15 - 25 - On the calibration of probabilistic classifier sets(2023)Volume: 206
Authors: Thomas Mortier, Viktor Bengs, Eyke Hüllermeier, Stijn Luca, Willem Waegeman
Pages: 8857 - 8870 - Valid prediction intervals for regression problems(2023)
Authors: Nicolas Dewolf, Bernard De Baets, Willem Waegeman
Pages: 577 - 613 - DeepMTP : a Python-based deep learning framework for multi-target prediction(2023)
Authors: Dimitrios Iliadis, Bernard De Baets, Willem Waegeman
- On second-order scoring rules for epistemic uncertainty quantification(2023)Volume: 202
Authors: Viktor Bengs, Eyke Hüllermeier, Willem Waegeman
Pages: 2078 - 2091