Tommaso Di Noia graduated in Electronic Engineering from the Polytechnic University of Bari in the academic year 2000/01 and obtained his PhD in Information Engineering in 2006.

Since 2005, he has been Assistant Professor (tenured), since 2014 an Associate Professor, and since 2018 a Full Professor in the Scientific Disciplinary Sector "Information Processing Systems" at the Polytechnic University of Bari.

His research currently focuses mainly on topics related to Artificial Intelligence and Data Management with reference to machine learning techniques and applications and recommendation systems. On the topic of personalized access to information and modeling of user preferences, innovative solutions have recently been proposed that combine and integrate different aspects, solutions, and techniques of Artificial Intelligence.
Of great interest to his research is the security and privacy of Artificial Intelligence systems with reference to Adversarial Machine Learning.
He has recently begun studying the information encoded in signals generated by the brain and their application in creative contexts such as automated music generation.

Initially, his research was dedicated to solving theoretical and practical problems in distributed resource retrieval and automatic reasoning scenarios. To verify the validity of the results obtained, they have always been implemented and tested in various application areas, such as e-commerce, business process management, web service discovery, and decision support systems for skills management in recruitment agencies. Subsequently, guided by the results obtained in e-commerce, his focus shifted to studying new ways of combining knowledge representation and automatic reasoning techniques, both for automated negotiation between rational agents with preferences and for ubiquitous scenarios and protocols.


Tommaso Di Noia is a reviewer for national and international research projects related to his research topics, for high-level international journals and conferences in the field of artificial intelligence, machine learning, the semantic web, and recommendation systems.

Google Scholar: https://scholar.google.it/citations?user=mPGG34oAAAAJ
Scopus: https://www.scopus.com/authid/detail.uri?authorId=6508366184
DBLP: https://dblp.org/pid/58/5192.html