Eco-aware GNN Recommenders

In this episode of Data Skeptic, we dive into eco-friendly AI with Antonio Purificato, a PhD student from Sapienza University of Rome. Antonio discusses his research on "EcoAware Graph Neural Networks for Sustainable Recommendations" and explores how we can measure and reduce the environmental impact of recommender systems without sacrificing performance.

Guest

Antonio Purificato: I am a second year PhD student in Data Science at Sapienza University of Rome in the Department of Computer, Control and Management Engineering. I am working under the guidance of Professor Fabrizio Silvestri. My research interests include Graph Neural Networks and training with noisy labels, with a focus on the environmental impact of deep learning algorithms. Prior to this, I completed my Master’s Degree in Artificial Intelligence and Robotics at Sapienza University of Rome.