Contributing to the 'Cellule de Coordination pour l'Intelligence Artificielle ', whose mission is (i) to enable the Université libre de Bruxelles community to consciously and responsibly harness the opportunities offered by Artificial Intelligence in their academic and professional activities, and (ii) to raise awareness and equip the university community with tailored training, resources, and tools, while fostering dialogue and co-creation to establish innovative and inclusive practices across the University.

Writing of a book on fraud detection for credit card transactions. Topics addressed: Performance metrics, model selection, imbalanced learning, feature engineering, deep learning, interpretability. https://github.com/Fraud-Detection-Handbook/fraud-detection-handbook

Blockchain-backed data authenticity for decisional algorithms. https://www.sensor.link.

Assisting in the design of AI-related pedagogical content for young and broad audiences.

Development of scalable fraud detection algorithms, from highly unbalanced, streaming data (BruFence project - Innoviris).

Development of a scalable (Big Data) infrastructure for storing, analyzing and sharing 'omics' data (BRiDGEIris project - Innoviris).

Distributed computing with Hadoop.

Development of serious video games for muscle spasticity rehabilitation (ICT4Rehab project, Innoviris).

Postdoctoral researcher for FWO, targeted at adaptive routing and online compression in wireless sensor networks.

Design of machine learning techniques (distributed compression and prediction) for environmental monitoring in wireless sensor networks. Marie Curie fellowship, COMP2SYS European project. PIMAN Project, Brussels Region.