Sotabase

Career

· Research Manager, KU Leuven2022–
· Postdoctoral Researcher, KU Leuven2020–2022
· Researcher, Acapela Group2019–2020
· PhD in Engineering Science: Computer Science: Machine Learning, KU Leuven2014–
· PhD Student, KU Leuven2014–2018
· Intern Programmer, VLIR-CPM2013–2013
· Master of Computer Science (Exchange), Ecole polytechnique fédérale de Lausanne (EPFL)2012–
· Master in Computer Science, KU Leuven2012–2014
· Employee, Danone2011–2012
· Laborer, Danone2009–2010
· Bachelor of Engineering: Computer Science and Electronics, KU Leuven2009–2012
· Waitress, Eatery De Werf2008–2008
· Youth Leader, Koning Kevin2006–2008
· Secondary school: Mathematics/Science, Sint-Albertus College2002–2008

Publications (38)

Learning from positive and unlabeled data: a survey
Machine-mediated learning · 2018
650
cited
Estimating the Class Prior in Positive and Unlabeled Data Through Decision Tree Induction
AAAI Conference on Artificial Intelligence · 2018
127
cited
Beyond the Selected Completely At Random Assumption for Learning from Positive and Unlabeled Data
ECML/PKDD · 2018
100
cited
Learning the Structure of Probabilistic Sentential Decision Diagrams
Conference on Uncertainty in Artificial Intelligence · 2017
94
cited
Tractable Learning for Complex Probability Queries
Neural Information Processing Systems · 2015
57
cited
A Scalable Ensemble Approach to Forecast the Electricity Consumption of Households
IEEE Transactions on Smart Grid · 2023
18
cited
Learning from Positive and Unlabeled Data under the Selected At Random Assumption
LIDTA@ECML/PKDD · 2018
17
cited
Positive and Unlabeled Relational Classification Through Label Frequency Estimation
International Conference on Inductive Logic Programming · 2017
9
cited
Interactive Multi-Level Prosody Control for Expressive Speech Synthesis
IEEE International Conference on Acoustics, Speech, and Signal Processing · 2022
7
cited
Optimizing workforce allocation under uncertain activity duration
Computers & industrial engineering · 2023
4
cited
Bagging Propensity Weighting: A Robust method for biased PU Learning
Learning with Imbalanced Domains: Theory and Applications · 2022
2
cited
Modeling PU learning using probabilistic logic programming
Machine-mediated learning · 2023
2
cited
Unifying Knowledge Base Completion with PU Learning to Mitigate the Observation Bias
AAAI Conference on Artificial Intelligence · 2022
2
cited
Learning from biased positive-unlabeled data via threshold calibration
International Conference on Artificial Intelligence and Statistics · 2025
1
cited
Measuring Adverse Drug Effects on Multimorbity using Tractable Bayesian Networks
arXiv.org · 2016
1
cited
Correction to: Modeling PU learning using probabilistic logic programming
Machine-mediated learning · 2025
Learning the structure of probabilistic SDDs
2016
Ordering-based search for tractable Bayesian networks
2015
ProbLog4Fairness: A Neurosymbolic Approach to Modeling and Mitigating Bias
arXiv.org · 2025
Sotabase