Projects

A selection of research and applied projects. See Publications for the full list of papers.

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.

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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.

Federated and Diversity-Aware Recommender Systems

Research on making recommender systems fairer and more diverse without sacrificing personalization. Topics include federated learning for Netflix-style recommendations, LLM-enhanced sequential recommendation, and personalization-aware methods for improving diversity.

Privacy-Preserving Synthetic Data

PhD and postdoctoral research on generating and evaluating synthetic data that protects individual privacy while remaining useful for downstream analysis. This work includes defenses against model inversion attacks and contributions to UNECE and IEEE synthetic-data guidelines.