Who am I
I am Giuseppe Spillo, a PhD Student in Computer Science at University of Bari, in the SWAP Research Group.
My main research areas are Knowledge-aware Recommender Systems, Multi-Modal Recommender Systems, and Knowledge Representation; I also study Green AI in recommendation scenario, and NLP (just for fun).
Check out my curriculum vitae!
A very special playlist based on Murubutu’s music, and an awsome italian hip-hop music playlist.
Short CV
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From October 2022 to now: Ph.D. Student in Computer Science at University of Bari.
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From April 2023 to now: Research assistant at the University of Bari.
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April 2022: Received master’s degree in Computer Science from the University of Bari. Thesis title: “Neuro-Symbolic Recommender Systems combining Graph Embeddings and First-Order Logic Rules.”
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October 2019: Received bachelor’s degree in Computer Science and Software Production Technologies from the University of Bari. Thesis title: “Exploiting Distributional Semantics to Generate Context-aware Explanations for Recommender Systems”
Main Research Interests
- Graph-based, Multi-modal and Knowledge-aware Recommendations
- Green AI
- Natural Language Processing
Latest Publications
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RecSys CarbonAtor: Predicting Carbon Footprint of Recommendation System Models, RecSoGood@RecSys24. To appear
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Towards Green Recommender Systems: Investigating the Impact of Data Reduction on Carbon Footprint and Algorithm Performances, RecSts 24: link!
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Recommender systems based on neuro-symbolic knowledge graph embeddings encoding first-order logic rules, UMUAI Journal: link!
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Evaluating Content-based Pre-Training Strategies for a Knowledge-aware Recommender System based on Graph Neural Networks, UMAP 24: link!
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Harnessing distributional semantics to build context-aware justifications for recommender systems, UMUAI Journal: link!
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Towards Sustainability-aware Recommender Systems: Analyzing the Trade-off Between Algorithms Performance and Carbon Footprint, RecSys 23: link!
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Combining Graph Neural Networks and Sentence Encoders for Knowledge-aware Recommendations, UMAP 23: link!
Best Student Paper Award Winner