Manel Slokom
Lecturer & Researcher, Hotelschool The Hague
As data and AI move into sensitive domains, I study how we can learn from data while better protecting the people behind it. My research develops and evaluates privacy-enhancing approaches, including federated learning and synthetic data, and connects them to responsible AI, fairness, and recommender systems. I apply this work across official statistics, digital media, and data governance. At the Research Centre of Hotelschool The Hague, I study personalization and customer satisfaction in HORECA, exploring how AI agents and technologies such as AR/VR can deepen our understanding of customer experiences. I hold a PhD in Computer Science from Delft University of Technology, supervised by Prof. Martha Larson. I am part of Hotelschool The Hague's Digitalization and Research group, where I teach Data Analytics and Research to first-year students and contribute to the Hospitality Research Lab for third-year students. Previously, I was a postdoctoral researcher at VU Amsterdam and CWI, and a methodologist at Statistics Netherlands (CBS). Connect with me.
Latest News
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Oct 2026
Paper accepted at BNAIC/BeNeLearn 2026
"Methodological Choices for Clustering-based Analysis of Classification Errors" by Mana Douma, Emma Beauxis-Aussalet, and Manel Slokom was accepted as a poster at BNAIC/BeNeLearn 2026.
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Oct 2026
SynIRgy to join ACM Web Conference 2027
Excited to announce that SynIRgy, the Workshop on Simulation and Synthetic Data for Information Retrieval, will return for a new edition at the ACM Web Conference 2027, following its successful debut at ECIR 2026.
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Aug 2026
Joined Hotelschool The Hague as Lecturer
Started as Lecturer at Hotelschool The Hague, teaching Data Analytics and Research, and contributing to the Hospitality Research Lab course and the maker space (AR/VR, 3D printing).
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Jul 2026
Best Paper Award at KES-HCIS
"LLMDiRec: LLM-Enhanced Intent Diffusion for Sequential Recommendation" (with Bo Chen) received the Best Paper Award at the KES International Conference on Human-Centered Intelligent Systems (KES-HCIS).
Projects
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SynIRgy: Simulation and Synthetic Data for Information Retrieval
SynIRgy is a workshop series I co-organize bringing together researchers working on simulation and synthetic data for information retrieval. The first edition ran at ECIR 2026 in Delft; a new edition is set to join the ACM Web Conference 2027.
COACH+: Human-in-the-Loop Output Checking
COACH+ automates statistical output checking for official statistics while keeping a human reviewer in the loop, balancing disclosure control with analyst efficiency. The work won the IAOS Prize for Young Statisticians.
Selected Publications
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Methodological Choices for Clustering-based Analysis of Classification Errors
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LLM-as-a-Discriminator: When Synthetic Tables Still Look Real
Paper Slides GitHub -
Beyond Centralization: User-Controlled Federated Recommendations in Practice
Paper Slides GitHub -
FedFlex: Federated Learning for Diverse Netflix Recommendations
Slides