Research Areas
Graph Counterfactual Explainability
Methods and frameworks (GRETEL, RSGG-CE) for explaining GNN decisions through counterfactual reasoning
Machine Unlearning
Selective data removal from trained models (ERASURE, ForSId) for GDPR compliance and responsible AI
Algorithmic Fairness
Detecting and mitigating bias in classification, search, and recommendation systems
Health Informatics
Syndromic surveillance from social media, drug repurposing via graph networks, disease-gene prediction
Temporal & Social Mining
Event discovery, hashtag sense clustering, topic detection in social streams and news media
Recommender Systems
Semantic recommendation, user profiling via taxonomies, enterprise social network analysis
Featured Projects
GRETEL Framework
An open-source framework for evaluating Graph Counterfactual Explanation methods. Provides building blocks to create bespoke explanation pipelines for GNN models.
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A fully extensible framework for Machine Unlearning, enabling selective removal of learned information from AI models for privacy compliance and bias mitigation.
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A novel Robust Stochastic Graph Generator for Counterfactual Explanations, producing plausible counterfactual examples from learned latent spaces. Published at AAAI 2024.
Learn moreFAIR-EDU
Promoting fairness in educational institutions by testing and estimating algorithmic bias in university staff-related data with a data- and model-agnostic approach.
Learn moreWorkshops & Events
WIPE-OUT 2026: 2nd Workshop on Machine Unlearning and Privacy Preservation
WIPE-OUT 2026 at ECML-PKDD 2026, September 7, 2026, Naples, Italy. Focusing on Machine Unlearning for privacy, bias m...
Unraveling Graph Counterfactual Explainability: from Theoretical Foundations to Technical Mastery (ECML-PKDD 2025)
Half-day tutorial at ECML-PKDD 2025 on Graph Counterfactual Explainability, covering theory and hands-on practice wit...
WIPE-OUT 2025: Workshop on Machine Unlearning Techniques
First edition of the WIPE-OUT workshop on Innovations, Privacy-preservation, and Evaluations Of machine Unlearning Te...
Machine Unlearning: Theory, Methods, and Evaluations with Hands-On Insights (ESSAI 2025)
PhD course on Machine Unlearning at the 3rd European Summer School on Artificial Intelligence (ESSAI 2025), June 30 -...