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Philippe BaeckeView profile

Professor

• Big Data Analytics
• Digital Marketing
• Customer Relationship Management
• +5 more

Philippe Baecke is a Professor of Business Analytics and Artificial Intelligence at Vlerick Business School, where he also serves as Programme Director for the Master in Business Analytics & AI and two executive programmes. He holds adjunct roles as Lecturer at Trinity Business School, Ireland, and Professor at the University of Namur. He earned his Doctorate in Applied Economics from Ghent University, complemented by an Advanced Master and Master in Applied Economics, both from Ghent University. His research focuses on leveraging big data analytics across marketing, operations, and finance, with specialties in digital marketing, customer relationship management, and network analysis. Notable areas include ad targeting, spatial modeling, and the application of AI in call center optimization and emotion recognition. He advises companies like KBC, ING, and Telenet on data strategy, blending strategic and operational insights. His recent work explores digital transformation trends, cost-effective AI adoption for SMEs, and the integration of human judgment in forecasting systems. He has published extensively in peer-reviewed journals, addressing topics like telecom data monetization, churn detection, and consumer privacy in addressable TV advertising. Baecke’s expertise also extends to vehicle telematics in insurance risk selection and spatial econometrics in customer acquisition modeling. He has collaborated on projects involving Bluetooth tracking in retail environments and the analysis of urbanization effects on customer behavior.

• Actuarial Science
• Machine Learning
• Insurance Pricing
• +3 more

Roel Henckaerts is a Research Fellow at the Insurance Research Group, KU Leuven. His work centers on integrating advanced computational methods with actuarial science to optimize insurance pricing models. Research Focus: Henckaerts specializes in machine learning applications for insurance, including telematics-based dynamic pricing, interpretable AI for regulated industries, and data-driven risk assessment. His methodologies emphasize neural networks, tree-based models, and transparent surrogate systems to balance accuracy with regulatory compliance. Publication Trends: Recent articles (2019–2025) demonstrate a shift toward neural networks and model interpretability, while earlier work (2016–2018) established foundations in tree-based methods and risk factor engineering. Thematic evolution shows consistent focus on bridging machine learning scalability with actuarial rigor. Affiliations: As part of KU Leuven's Insurance Research Group, Henckaerts collaborates on industry-facing projects, though specific lab/team structures are undisclosed.

• Machine Learning
• Artificial Intelligence
• Fraud Detection
• +7 more

Bart Baesens is a full professor at the Faculty of Economics and Business (FEB) at KU Leuven, affiliated with the Information Systems Engineering Research Group (LIRIS). He is a member of Leuven.AI, the university's artificial intelligence institute, and leads the education commission for the Master in Information Management program at FEB. His research focuses on machine learning, fraud detection, credit risk, network analytics, and explainable AI, with applications in finance, insurance, agriculture, and smart systems. Baesens is known for developing frameworks like IML4DQ and GARG-AML, and has contributed to foundational work in sensor data analysis and graph-based learning for AML systems. His recent research emphasizes practical applications of AI, such as improving museum archive accessibility via large language models and enhancing agricultural sustainability through precision irrigation systems. He collaborates with industry partners on projects like predictive maintenance optimization and customer lifetime value modeling, leveraging techniques like temporal fusion transformers and self-supervised anomaly detection. Baesens' work bridges academia and industry, with publications addressing ethical AI, model interpretability, and real-world fraud detection challenges. His contributions span over 150 peer-reviewed articles, including influential studies on credit scoring, social network analytics for insurance fraud, and multi-task learning for environmental monitoring.

Bart CockxView profile

Professor

• Labor Economics
• Public Economics
• Social Policy
• +3 more

Bart Cockx is a full professor in the Department of Economics at Ghent University and an associate researcher at IRES/LIDAM, UCLouvain. His academic career centers on empirical labor economics with a focus on Belgian social security systems and labor market policies. His research spans unemployment insurance design, job search activation policies, youth integration programs, and ethnic discrimination in labor markets. Key methodologies include quasi-experimental designs and administrative data analysis, particularly examining how benefit structures and monitoring requirements affect employment outcomes. He frequently investigates policy responses to economic shocks like the COVID-19 pandemic. Analysis of his 15 most recent publications reveals consistent emphasis on evaluating active labor market interventions through rigorous econometric methods. Dominant themes include benefit sanction effects, big data applications in job matching, pandemic-era policy adaptations, and structural barriers facing vulnerable groups like youth and ethnic minorities. His work demonstrates strong policy relevance with direct implications for Belgian welfare reforms.

Jan DhaeneView profile

Professor

• Actuarial Sciences
• Financial Mathematics
• Fair Valuation
• +3 more

Jan Dhaene is a full professor at the Faculty of Economics and Business (FEB) at KU Leuven, Belgium. He leads the Insurance Research Group and holds roles as coordinator of the group and head of the Division of Actuarial Applications for Insurance Companies and Pension Fund Management. His research focuses on actuarial sciences, financial mathematics, fair valuation, comonotonicity, and risk-sharing mechanisms. He actively participates in institutional governance through roles like member of the Faculty Council and Programme Committee for the Master in Actuarial and Financial Sciences. Recent projects include exploring competitive equilibrium in insurance markets, peer-to-peer insurance risk pooling, and causal machine learning applications in finance. He has published extensively on topics such as quantile risk-sharing rules, collaborative insurance models, and herd behavior in stock markets. His work bridges theoretical actuarial science with practical insurance market challenges, emphasizing fairness, systemic risk analysis, and innovative risk-sharing frameworks. Notable contributions include developing the herd behavior index (HBI) to measure co-movement in financial markets and advancing methodologies for fair valuation of insurance liabilities. He collaborates internationally and serves as promotor/co-promotor in multiple research projects funded by national and institutional grants.

Katrien AntonioView profile

Professor

• Insurance Analytics
• Data Science
• Predictive Modeling in Insurance
• +3 more

Katrien Antonio is a **full professor** in actuarial science and insurance analytics at **KU Leuven** and holds a **part-time professorship** in actuarial data science at the University of Amsterdam. She leads the **Insurance Research Group** and chairs the **Department of Accountancy, Finance and Insurance** within the **Faculty of Economics and Business (FEB)**. Her roles include directing the LRISK research center and overseeing education commissions at KU Leuven’s Leuven and Kortrijk campuses. **Research Interests**: Insurance analytics, data science, predictive modeling in insurance, actuarial science, and sustainable finance. Key projects include designing inclusive insurance products, compliant actuarial models, and risk analytics for societal impact. **Publications**: Her recent work focuses on environmental impacts on mortality, neural networks for insurance pricing, fraud detection, and IoT-driven maintenance risk assessment. She has published in top journals like *Journal of the Royal Statistical Society*, *North American Actuarial Journal*, and *European Journal of Operational Research*. **Education**: PhD in Mathematics (KU Leuven, 2007), with prior degrees in Mathematics from the same institution. Extensive teaching experience across higher education, emphasizing data-driven insights and innovative materials. **Grants & Projects**: Leads initiatives such as the “Actuaries and STatisticians” project (2022–2025) and “VALERIA” (2021–2024), focusing on emerging risks and sustainable finance. **Labs & Teams**: Directs the LRISK center, fostering interdisciplinary collaboration in risk analysis. Active in academic networks, including IMAC and the Faculty Board of Economics and Business.

Christian ColotView profile

Researcher

• Data Mining
• Social Network Analysis
• Marketing
• +4 more

Christian Colot is a researcher at the Namur Institute for Complex Systems (University of Namur) with a focus on data mining, social network analysis, and decision support systems. His work bridges telecom data analytics, marketing, and credit risk, emphasizing data monetization and churn detection. Key Research Areas : Data Mining, Telecom Data Monetization, Churn Detection, Decision Support Systems. Notable Projects : Leveraging Mobile Data for Churn Detection (2015–2020), Network-Based Metrics for Decision Support (2022). Scientific Recognition : Nominated for the Dauby Award for his master's thesis. Conference Contributions : Presented at international events including ICDSST 2017 and SEKE 2022. His recent publications highlight innovative approaches to mobile data analysis, social influence disentanglement, and metaphor computational modeling. Collaborations with IBM and telecom stakeholders underscore his industry impact.

• Corporate Finance
• Environmental Economics
• Insolvency Procedures
• +5 more

Nico Dewaelheyns serves as a Professor at KU Leuven's Faculty of Economics and Business (FEB), holding dual appointments at both the Antwerp (Hendrik Conscienceplein 8) and Leuven (Naamsestraat 69) campuses. He chairs the Department of Accountancy, Finance and Insurance and leads the Subdivision 4 at Antwerp Campuses, while also serving on the Council of the Faculty of Economics and Business and the Campus Council FEB. His research spans corporate finance, environmental economics, and insolvency procedures, with particular focus on carbon risk in the EU Emissions Trading Scheme, SME financial decision-making, and business restructuring. Current projects include 'Sustainability and private firms’ financial decision making' (2024-2028) and 'Domain-Specific Database Infrastructure for Empirical Research' (2024-2030). Analysis of his recent publications reveals strong interdisciplinary work bridging climate policy and finance, with recurring themes in carbon risk valuation, SME insolvency dynamics, and environmental regulation impacts. His research frequently employs empirical analysis of Belgian SMEs within EU regulatory frameworks. As an academic leader, Dewaelheyns supervises doctoral candidates including J. Boeckx (Employment Downsizing), K. Struyfs (Environmental Regulation), and M. Verreydt (Time-to-Failure Analysis), while teaching courses in Contemporary Issues in Finance, Investment Analysis, and Corporate Finance. His laboratory work centers on the Finance Research Group, which investigates empirical finance questions using specialized databases, with particular emphasis on the intersection of environmental policy and corporate financial behavior.

• genomics
• digital health
• health humanities
• +4 more

Ine Van Hoyweghen is a full professor at the Faculty of Social Sciences, KU Leuven , and head of the Life Sciences & Society Lab . She serves as a member of multiple institutes including the Leuven Centre for Health Humanities , DigiSoc , and iSi Health , with a focus on the ethical, legal, and social implications of digital and genomic medicine. Research Focus: Genomics, digital health, health humanities, responsible innovation Leadership: Life Sciences & Society Lab; involved in EU health data policy initiatives Awards: Francqui Prize in Human Sciences (2025) Her recent work explores in silico medicine , next-generation sequencing implementation , and genetic discrimination policy , emphasizing cross-disciplinary collaboration and public values in algorithmic healthcare. Publications address European Health Data Space challenges and genomic diagnostic ethics . Notable scientific awards include the 2025 Francqui Prize, recognizing her contributions to human sciences. She actively engages in EU policy debates through projects like REIMAGINE ADM and NEUROCOV , with a focus on stakeholder engagement and trust-building in digital medicine.