Davide Abbattista

I am a Data and Artificial Intelligence Researcher with a Master’s degree in Computer Science Engineering from the Polytechnic of Bari, specializing in Artificial Intelligence and Data Science. During my academic journey, I collaborated on several team projects, sharpening my skills in AI, Machine Learning, Deep Learning, Data Science, and Recommender Systems.

As part of my master’s program, I completed a research period at the University of Glasgow, where I developed my thesis on Deep Learning. This research culminated in a paper published at RecSys ’24. Additionally, my team’s contributions to the RecSys Challenge ’24 were accepted for publication, reflecting our innovative work in recommender systems.

My technical expertise centers on Python as my primary programming language, with extensive experience using the PyTorch ML library for developing and optimizing advanced machine learning models. I am passionate about leveraging AI technologies to tackle complex real-world challenges and am eager to contribute to innovative projects in this dynamic field.

news

Dec 09, 2024	I’ve started a new position as Data and AI Reseacher at Engineering!
Aug 29, 2024	Enhancing Sequential Music Recommendation with Personalized Popularity Awareness accepted for publication in the RecSys 2024 LBR track!
Aug 03, 2024	DIVAN: Deep-Interest Virality-Aware Network to Exploit Temporal Dynamics in News Recommendation accepted for publication in the RecSys Challenge 2024 Workshop!

selected publications

RecSys

Enhancing Sequential Music Recommendation with Personalized Popularity Awareness

Davide Abbattista, Vito Walter Anelli, Tommaso Di Noia, Craig MacDonald, and Aleksandr Vladimirovich Petrov

In RecSys, 2024

Bib PDF

@inproceedings{DBLP:conf/recsys/AbbattistaANMP24,
  author = {Abbattista, Davide and Anelli, Vito Walter and Noia, Tommaso Di and MacDonald, Craig and Petrov, Aleksandr Vladimirovich},
  title = {Enhancing Sequential Music Recommendation with Personalized Popularity Awareness},
  booktitle = {RecSys},
  pages = {1168--1173},
  publisher = {{ACM}},
  year = {2024},
}

RecSys Challenge

DIVAN: Deep-Interest Virality-Aware Network to Exploit Temporal Dynamics in News Recommendation

Antonio Ferrara, Marco Valentini, Paolo Masciullo, Antonio De Candia, Davide Abbattista, Riccardo Fusco, Claudio Pomo, Vito Walter Anelli, Giovanni Maria Biancofiore, Ludovico Boratto, and Fedelucio Narducci

In RecSys Challenge, 2024

Bib PDF

@inproceedings{DBLP:conf/recsys/FerraraVMCAFPAB24,
  author = {Ferrara, Antonio and Valentini, Marco and Masciullo, Paolo and Candia, Antonio De and Abbattista, Davide and Fusco, Riccardo and Pomo, Claudio and Anelli, Vito Walter and Biancofiore, Giovanni Maria and Boratto, Ludovico and Narducci, Fedelucio},
  title = {{DIVAN:} Deep-Interest Virality-Aware Network to Exploit Temporal
                    Dynamics in News Recommendation},
  booktitle = {RecSys Challenge},
  pages = {12--16},
  publisher = {{ACM}},
  year = {2024},
}