Human-centred AI for human-machine collaboration - Prof. Sotiris Manitsaris

Place: Room 3.216 - Campus Grand Paris et online

Time: 12pm - 1:30pm

Speaker: Prof. Sotiris Manitsaris- Director of Centre for Robotics - Mines Paris, PSL Université

Discussant : Jean-Philippe Courtois - Executive VP Microsoft - President Association Live for Good

Biography of the speaker :

Dr. Sotiris Manitsaris is Senior Researcher and Science-Technology Project and Team Leader at the Centre for Robotics of MINES ParisTech, Université PSL. He holds a University Degree in Applied Mathematics from the Aristotle University of Thessaloniki, a double Master Degree in Local Development from the University of Blaise-Pascal and the Engineering School of the University of Thessaly and a PhD in Computer Science – Artificial Intelligence from the University of Macedonia. He participated in projects as postdoctoral fellow in Human-Robot Collaboration for the Industry 4.0, the Biomedical Engineering and the Creative and Cultural Industries. He is currently involved in a number of H2020 projects and he has strong collaboration with startups and industrial groups, such as PSA, CRF, SAGEM and a number of Creative and Cultural Industries. His research focuses on movement-based human-machine collaboration and Human-Centred Artificial Intelligence in general. He leads the Post-Master’s Degree AIMove – “Artificial Intelligence and Movement in Industries and Creation”, which is supported by European academic and professional leaders of the field. Moreover, he is the President of the GAIIA Association (Gesture & AI in Industry and Arts) and the Head of IT researchers group at the ElonTech Observatory in law and new technologies.

Abstract :

The presentation focuses on human-machine collaboration in real-world industrial environments, emphasizing Human-Centered Artificial Intelligence (HAI). The aim is to enable partnerships in which machines can understand and anticipate human behaviors, responding appropriately. This presentation is guided by two main hypotheses concerning movement-based collaboration: 1) can a machine learn to recognize expert actions? and 2) can standard instrumented interactions (e.g., through buttons and similar controls) be replaced by HAI-driven embodied interactions? These hypotheses were validated through experiments in fields such as human-robot collaboration, computer-mediated human learning, and digital musical instruments.

For further information, please contact Professor Margherita Pagani: margherita.pagani@skema.edu