Introducing Alessandro Sbandi : a PhD student in Artificial Intelligence at Sapienza, working at TIM Official. His research interests are #GNNs and #reinforcement learning recommender systems. He has a degree in #Physics. #PhD #RL #AI

Thrilled to announce our paper "Mitigating Extreme Cold Start in Graph-based RecSys through Re-ranking" has been accepted at CIKM 2024! 🎉 Co-authored by Alessandro Sbandi (❖,❖) , Federico Siciliano , and Fabrizio Silvestri . Stay tuned for more updates! #CIKM2024 #RecommenderSystems

"Eco-Aware Graph Neural Networks for Sustainable Recommendations", co-authored by Antonio Purificato and Fabrizio Silvestri has been accepted for the #RecSoGood workshop located at #RecSys24 ACM RecSys. See you in Bari !!! #PhD #GNN #Recommendation #Research

Exciting news! Alessandro Sbandi will be presenting our paper "Mitigating Extreme Cold Start in Graph-based RecSys through Re-ranking" at #CIKM2024 in Boise, Idaho, accepted to the Applied Research Track. Stop by and say hello! 👋 #RecSys #ResearchPapers dl.acm.org/doi/10.1145/36…

Super proud to show Alessandro Sbandi from our group, presenting the paper “Mitigating Extreme Cold Start in Graph-based RecSys through Re-ranking” at ACM CIKM 2024 , in Bodo, co-authored with Fabrizio Silvestri and Federico Siciliano . Link to the paper: dl.acm.org/doi/pdf/10.114….

📢 Our TIM-Rec dataset has been accepted at the ACM RecSys 2025 Resource Track! TIM-Rec tackles multi-item upselling in a Telco setting with sparse feedback, a real-world challenge for recommender systems. Congrats to the team Alessandro Sbandi Federico Siciliano Fabrizio Silvestri! #RS