Claudio Pomo

WORK HISTORY

EDUCATION

SKILLS

ABOUT CLAUDIO POMO

As an Assistant Professor at Politecnico di Bari, my research is rooted in the intersections of artificial intelligence (AI), machine learning (ML), and recommender systems. My work focuses on solving complex real-world problems by developing scalable, cutting-edge algorithms that enhance the quality of recommendations, personalization, and user engagement. Over the past decade, I have explored various methodologies, from collaborative filtering and matrix factorization to more advanced techniques like graph neural networks (GNNs) and reinforcement learning.My contributions have been published in top-tier journals and conferences, and I have been actively involved in shaping the discourse around recommender systems through my work with the RecSys Challenge, a leading competition that brings together industry and academia to push the boundaries of recommender technology. I have led and participated in projects aimed at improving the efficiency of recommendation engines, reducing computational costs, and enhancing their interpretability.Technical Expertise:Recommender Systems (Collaborative Filtering, Matrix Factorization, GNNs, Sequence Models)Machine Learning and Deep Learning (Supervised, Unsupervised, Reinforcement Learning)Data Processing at Scale (Big Data Architectures, Distributed Systems)AI Ethics (Fairness, Transparency, Bias in Algorithms)Research Leadership and Collaboration (Industry-Academia Partnerships, Project Management)