Hello, I am Matteo Attimonelli, currently pursuing a Ph.D. in Artificial Intelligence as part of the National Ph.D. Program at Sapienza University of Rome. I am based at the Polytechnic University of Bari within the Information Systems Research Group (SisInfLab), lead by Prof. Tommaso Di Noia.

As a passionate enthusiast of Deep Learning, I have actively engaged in Research and Development (R&D) activities within the academic realm, contributing to university projects and a research internship in the INFSYS Lab, supervised by Prof. Dietmar Jannach. Furthermore, I’ve had the opportunity to work in a company, contributing to the development of Deep Learning solutions for Computer Vision and Recommender Systems domains.

Currently, my primary research focuses on Generative Artificial Intelligence, Multimodal Deep Learning, and Recommender Systems.

Recent publications

Bold style means (one of) main author(s).

• Do Recommender Systems Really Leverage Multimodal Content? A Comprehensive Analysis on Multimodal Representations for Recommendation
  Pomo Claudio, Attimonelli Matteo, Danese Danilo, Narducci Fedelucio, Di Noia Tommaso
  In Proceedings of the 34th ACM International Conference on Information and Knowledge Management (CIKM ’25), November 10–14, 2025, Seoul, Republic of Korea.

• Do We Really Need Specialization? Evaluating Generalist Text Embeddings for Zero-Shot Recommendation and Search
  Attimonelli Matteo, De Bellis Alessandro, Pomo Claudio, Jannach Dietmar, Di Sciascio Eugenio, Di Noia Tommaso
  In Proceedings of the Nineteenth ACM Conference on Recommender Systems (RecSys ’25), September 22–26, 2025, Prague, Czech Republic.

• Standard Practices for Data Processing and Multimodal Feature Extraction in Recommendation with DataRec and Ducho (D&D4Rec)
  Mancino Alberto Carlo Maria, Attimonelli Matteo, Di Fazio Angela, Malitesta Daniele, Di Noia Tommaso
  In Proceedings of the Nineteenth ACM Conference on Recommender Systems (RecSys ’25), September 22–26, 2025, Prague, Czech Republic.

• Ducho 2.0: Towards a More Up-to-Date Feature Extraction and Processing Framework for Multimodal Recommendation
  Attimonelli Matteo, Danese Danilo, Malitesta Daniele, Pomo Claudio, Gassi Giuseppe, Di Noia Tommaso
  WWW ‘24 Companion, May 13-17, 2024, Singapore.

• Adversarial Attacks Against Visually Aware Fashion Outfit Recommender Systems
  Attimonelli Matteo, Amatulli Gianluca, Di Gioia Leonardo, Malitesta Daniele, Deldjoo Yashar, Di Noia Tommaso
  Recommender Systems in Fashion and Retail. RECSYS 2022.

Contacts

• institutional email: matteo.attimonelli@poliba.it
• institutional webpage: https://sisinflab.poliba.it/people/matteo-attimonelli/