MATTEO MENOLOTTO received the B.Eng. in electronic engineering from the University of Trieste in 2011 and M.Eng. degrees in biomedical engineering with industrial curriculum from the University of Pisa in 2015. In 2020 he received his Ph.D. at the University of Strathclyde, Glasgow, UK, in biomedical engineering on digital image processing and wearable technology topics. Since 2019 he has been a Research Assistant, first with the Biomedical Engineering Department of University of Strathclyde, and then postdoctoral researcher with the Tyndall National Institute, University College of Cork, Cork, Ireland since 2020. His research interests include image processing, image filtering, portable device for medical applications, wearable sensors and robotics. Currently his research activity involves the development of AI-based collaborative robotics strategies for industry 4.0 applications (CONFIRM SFI). In particular, the use of multimodal datasets, such as human-centric data (e.g. IMU, EMG, pressure insole) and vision-based data (e.g. motion tracking, gaze), to train machine learning networks to recognize patterns associated with risks factors and human intention, to improve the collaboration behaviour and the safe operation of collaborative robots in the contest of smart manufacturing.