معرفی
Vito Walter Anelli is an Assistant Professor specializing in the technical and ethical aspects of Recommender Systems. His work focuses on fairness, privacy, adversarial robustness, and regulatory compliance in AI-driven recommendation frameworks. He actively contributes to the development of evaluation methodologies, frameworks for reproducible research, and counterfactual reasoning techniques to assess model fairness.
His research spans multiple domains including federated learning for privacy preservation, adversarial attacks on visual and graph-based recommenders, and applications in healthcare such as predicting kidney disease progression. He has organized workshops on Knowledge-Aware Recommender Systems (KaRS) and contributed to conferences like RecSys and Dagstuhl Seminars.
Anelli's publications emphasize interdisciplinary approaches, blending computer science with legal and ethical considerations. He has developed frameworks like ELLIOT for rigorous recommender system evaluation and explored the integration of knowledge graphs to enhance recommendation interpretability and user control over data.
Key themes in his work include addressing bias in graph collaborative filtering, auditing algorithmic fairness in compliance with regulations, and advancing techniques to protect against adversarial manipulation. His contributions bridge technical innovation with societal impact, particularly in ensuring transparency and accountability in AI systems.
