As of July 1st 20201, I am the Lead of the RobotLearn Team at Inria Grenoble Rhône-Alpes. RobotLearn’s main ambition is to train robots to acquire the capacity to look, listen, learn, move and speak in a socially acceptable manner. This will be achieved via a fine tuning between scientific findings, development of practical algorithms and associated software packages, and thorough experimental validation. It is planned to endow robotic platforms with the ability to perform physically-unconstrained and open-domain multi-person interaction and communication. We will explore novel scientific research opportunities at the crossroads of discriminative and generative deep learning architectures, Bayesian learning and inference, computer vision, audio/speech signal processing, spoken dialog systems, and robotics. The paramount applicative domain of RobotLearn is the development of multimodal and multi-party interactive methodologies and technologies for social (companion) robots.