Talk by Prof. Mohamed Chetouani, Sorbonne University, Paris, France

Interpersonal Human-Robot Interaction & Engagement

Synchrony, engagement and learning are important abilities that allow sustaining dynamics of social interaction. In this talk, we will address these topics with an interpersonal interaction point of view. In particular, we will introduce interpersonal human-machine interactions schemes and models with a focus on definitions, sensing and evaluations of social signals and behaviors. We will show how these models are currently applied to detect engagement in multi-party human-robot interactions, detect human’s personality traits and task learning.

Prof. Mohamed Chetouani is the head of the IMI2S (Interaction, Multimodal Integration and Social Signal) research group at the Institute for Intelligent Systems and Robotics (CNRS UMR 7222), Sorbonne University. He is currently a Full Professor in Signal Processing and Machine Learning for Human-Machine Interaction. He is also CSO at Batvoice Technologies. His research activities cover the areas of social signal processing, social robotics and interactive machine learning with main applications in psychiatry, psychology, social neuroscience and education. In 2016, he was a Visiting Professor at the Human Media Interaction group of University of Twente (NL). He is the Deputy Director of the Laboratory of Excellence SMART Human/Machine/Human Interactions In The Digital Society. He coordinates the Autonomy Programme of the Institute of Engineering for Health at Sorbonne University. Since 2018, he is the coordinator of the ANIMATAS H2020 Marie Sklodowska Curie European Training Network.