Professor Angelo Cangelosi

Angelo Cangelosi


Turing Fellow

Partner Institution


Angelo Cangelosi is Professor of Machine Learning and Robotics at the University of Manchester. Previously he was Professor of Artificial Intelligence and Cognition, and founding director, at the Centre for Robotics and Neural Systems at Plymouth University. Cangelosi studied Psychology and Cognitive Science at the Universities of Rome La Sapienza and at the University of Genoa, and was visiting scholar at the University of California San Diego and the University of Southampton. Currently, he is the coordinator of the EU H2020 Marie Sklodowska-Curie European Industrial Doctorate “APRIL: Applications of Personal Robotics through Interaction and Learning” (2016-2019).

He is also Principal Investigator for the ongoing projects “THRIVE++” (US Air Force Office of Science and Research, 2014-2022), the H2020 project MoveCare, and the Marie Curie projects SECURE and DCOMM. He has secured over £30m of research grants as coordinator/PI. Cangelosi has produced more than 250 scientific publications. In 2012-13 he was Chair of the IEEE Technical Committee on Autonomous Mental Development. He has been Visiting Professor at Waseda University in Japan and at Sassari and Messina Universities in Italy. Cangelosi is Editor of the following journals “Interaction Studies” and “IET Cognitive Computation and Systems”, and in 2015 was Editor-in-Chief of IEEE Transactions on Autonomous Development. His latest book “Developmental Robotics: From Babies to Robots” (MIT Press; co-authored with Matt Schlesinger) was published in January 2015, and recently translated in Chinese and Japanese.

Research interests

Cangelosi's main research interests are in artificial intelligence and cognitive robotics. He is one of the pioneers in the field of developmental robotics, with his main scientific work on neuro-robotic modelling of the grounding of language and of embodies cognition. Application areas include social robot companion for health and social care, and trust and acceptability in human-robot interaction.