Federico Siciliano

Federico Siciliano is a Postdoctoral Researcher and Ricercatore (Researcher) at Sapienza University of Rome, affiliated with the RSTLess Lab under the supervision of Prof. Fabrizio Silvestri. He has been teaching Algorithmic Methods of Data Mining in the Master’s program in Data Science since 2024. His research spans recommender systems, information retrieval, explainable AI, and deep learning theory.

Education:

• PhD in Data Science, Sapienza University of Rome (2020–2024)
• Master’s in Data Science, Sapienza University of Rome (2017–2019)
• Bachelor’s in Management Statistics, Sapienza University of Rome (2014–2017)

His research interests lie at the intersection of Artificial Intelligence and Data Science, particularly focusing on sequential and graph-based recommender systems, robustness and explainability in AI models, and theoretical foundations of deep learning. His recent work explores architectural improvements in RAG systems, anomaly detection in 5G networks, and trustworthy AI through counterfactual explanations.

The most recent publications (2023–2025) reveal a strong trend toward robust and interpretable AI systems, with recurring themes in recommendation, retrieval, and security. His work combines theoretical rigor with practical applications in healthcare, telecommunications, and misinformation detection. He frequently publishes in high-impact venues such as IEEE Access, ACM RecSys, and CVPR.

Scientific Collaborations:

• University of Cambridge
• Meta
• Amazon
• University of Pisa (UniPi)
• INAF (Italian National Institute of Astrophysics)

Federico actively contributes to the research community by organizing a special session on Neural Methods for IR and RecSys at IJCNN 2025. He has been involved in projects related to space weather monitoring and clinical outcome prediction in thyroid cancer. No formal students or grants are explicitly mentioned, but his collaborative projects suggest involvement in externally funded research.

Laboratories and Teams:

• RSTLess Lab, Sapienza University of Rome