Selected Publications
2026
Would a Large Language Model Pay Extra for a View? Inferring Willingness to Pay from Subjective Choices
arXiv ↗All Publications
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2026
Calculating and Visualizing Feature Importance Values for Counterfactual Explanations
Paper ↗ -
2026
Voluntary Tax Disclosures of Listed Companies in Europe
Paper ↗ -
2026
Would a Large Language Model Pay Extra for a View? Inferring Willingness to Pay from Subjective Choices
arXiv ↗ -
2026
Reranking individuals: The effect of fair classification within-groups
Paper ↗ -
2026
Fairness principles across contexts: evaluating gender disparities of facts and opinions in large language models
Paper ↗ -
2026
Adapting Multiverse Analysis for Prediction: A Decision-Maker's Dashboard
Paper ↗ -
2025
Monetization could corrupt algorithmic explanations
Paper ↗ -
2025
One world, one opinion? The superstar effect in LLM responses
Paper ↗ -
2025
The impact of cloaking digital footprints on user privacy and personalization
Paper ↗ -
2025
Words reveal wants: How well can simple LLM-based AI agents replicate people's choices based on their social media posts
Paper ↗ -
2025
What If the Prompt Were Different? Counterfactual Explanations for the Characteristics of Generative Outputs
Paper ↗ -
2025
Tell me a story! Narrative-driven XAI with Large Language Models
Paper ↗ -
2025
GraphXAIN: narratives to explain graph neural networks
Paper ↗ -
2025
Exposing Shortcuts in Image Classification by Aggregating Counterfactuals
Paper ↗ -
2024
PreCoF: counterfactual explanations for fairness
Paper ↗ -
2024
Explainable AI for operational research: A defining framework, methods, applications, and a research agenda
Paper ↗ -
2024
Disagreement amongst counterfactual explanations: how transparency can be misleading
Paper ↗ -
2024
Can metafeatures help improve explanations of prediction models when using behavioral and textual data?
Paper ↗ -
2024
A model-agnostic and data-independent tabu search algorithm to generate counterfactuals for tabular, image, and text data
Paper ↗ -
2023
The privacy issue of counterfactual explanations: explanation linkage attacks
Paper ↗ -
2023
Manipulation risks in Explainable AI: The implications of the disagreement problem
Paper ↗ -
2023
Explainability Methods to Detect and Measure Discrimination in Machine Learning Models
Paper ↗ -
2023
AI can be both accurate and transparent
Paper ↗ -
2022
Explainable image classification with evidence counterfactual
Paper ↗ -
2022
The non-linear nature of the cost of comprehensibility
Paper ↗ -
2022
Data science ethics: Concepts, techniques, and cautionary tales
Book ↗ -
2022
Barriers to academic data science research in the new realm of algorithmic behaviour modification by digital platforms
Paper ↗ -
2021
A framework and benchmarking study for counterfactual generating methods on tabular data
Paper ↗ -
2021
How to choose an explainability method? Towards a methodical implementation of XAI in practice
Paper ↗ -
2021
Explainable AI for psychological profiling from behavioral data: An application to big five personality predictions from financial transaction records
Paper ↗ -
2021
Patterns of democracy? Social network analysis of parliamentary Twitter networks in 12 countries
Paper ↗ -
2021
Predictive modeling to study lifestyle politics with Facebook likes
Paper ↗ -
2021
Node classification over bipartite graphs through projection
Paper ↗ -
2020
A comparison of instance-level counterfactual explanation algorithms for behavioral and textual data: SEDC, LIME-C and SHAP-C
Paper ↗ -
2020
Value-added tax fraud detection with scalable anomaly detection techniques
Paper ↗ -
2020
Efficient parcel delivery by predicting customers' locations
Paper ↗ -
2020
A benchmarking study of classification techniques for behavioral data
Paper ↗ -
2019
What does your Facebook profile reveal about your creditworthiness? Using alternative data for microfinance
Paper ↗ -
2019
Retail credit scoring using fine-grained payment data
Paper ↗ -
2019
Customs fraud detection: Assessing the value of behavioural and high-cardinality data under the imbalanced learning issue
Paper ↗ -
2019
Deep learning on big, sparse, behavioral data
Paper ↗ -
2018
Belgian economic policy uncertainty index: Improvement through text mining
Paper ↗ -
2018
Imbalanced classification in sparse and large behaviour datasets
Paper ↗ -
2018
Wallenius Bayes
Paper ↗ -
2017
Bankruptcy prediction for SMEs using relational data
Paper ↗ -
2017
Between hawks and doves: measuring central bank communication
Paper ↗ -
2017
RULEM: A novel heuristic rule learning approach for ordinal classification with monotonicity constraints
Paper ↗ -
2016
Mining Massive Fine-Grained Behavior Data to Improve Predictive Analytics
Paper ↗ -
2016
Explaining Classification Models Built on High-Dimensional Sparse Data
arXiv ↗ -
2015
Including high-cardinality attributes in predictive models: A case study in churn prediction in the energy sector
Paper ↗ -
2015
Comprehensible software fault and effort prediction: A data mining approach
Paper ↗ -
2015
Finding similar mobile consumers with a privacy-friendly geosocial design
Paper ↗ -
2015
Loyal to your city? A data mining analysis of a public service loyalty program
Paper ↗ -
2015
Active learning-based pedagogical rule extraction
Paper ↗ -
2015
To tune or not to tune: rule evaluation for metaheuristic-based sequential covering algorithms
Paper ↗ -
2014
Explaining data-driven document classifications
Paper ↗ -
2014
Evaluating and understanding text-based stock price prediction models
Paper ↗ -
2014
Social network analysis for customer churn prediction
Paper ↗ -
2014
Corporate residence fraud detection
Paper ↗ -
2014
Forecasting Loss Given Default models: impact of account characteristics and the macroeconomic state
Paper ↗ -
2013
Predictive Modeling With Big Data: Is Bigger Really Better?
Paper ↗ -
2013
A novel credit rating migration modeling approach using macroeconomic indicators
Paper ↗ -
2012
New insights into churn prediction in the telecommunication sector: A profit driven data mining approach
Paper ↗ -
2012
Benchmarking regression algorithms for loss given default modeling
Paper ↗ -
2012
Media coverage in times of political crisis: A text mining approach
Paper ↗ -
2011
Building comprehensible customer churn prediction models with advanced rule induction techniques
Paper ↗ -
2011
Editorial survey: swarm intelligence for data mining
Paper ↗ -
2011
Data mining techniques for software effort estimation: a comparative study
Paper ↗ -
2011
Performance of classification models from a user perspective
Paper ↗ -
2011
Identifying financially successful start-up profiles with data mining
Paper ↗ -
2010
An overview and framework for PD backtesting and benchmarking
Paper ↗ -
2010
Credit rating prediction using ant colony optimization
Paper ↗ -
2010
From linear to non-linear kernel based classifiers for bankruptcy prediction
Paper ↗ -
2009
Robust Process Discovery with Artificial Negative Events
Paper ↗ -
2009
50 years of data mining and OR: upcoming trends and challenges
Paper ↗ -
2009
Inferring comprehensible business/ICT alignment rules
Paper ↗ -
2008
Decompositional rule extraction from support vector machines by active learning
Paper ↗ -
2008
Predicting going concern opinion with data mining
Paper ↗ -
2008
Mining software repositories for comprehensible software fault prediction models
Paper ↗ -
2007
Comprehensible credit scoring models using rule extraction from support vector machines
Paper ↗ -
2007
Classification with ant colony optimization
Paper ↗ -
2007
Forecasting and analyzing insurance companies' ratings
Paper ↗ -
2006
Ant-based approach to the knowledge fusion problem
Paper ↗ -
2006
Country corruption analysis with self organizing maps and support vector machines
Paper ↗ -
2005
New trends in data mining
Paper ↗ -
2005
Benchmarking state-of-the-art classification techniques for credit scoring