Keynote

1. Is the autonomous social robot within reach?
2. Social Signals as a Facilitator of Human-Robot Interaction

Is the autonomous social robot within reach?

Abstract
The study of Human-Robot Interaction focuses on how people respond to interacting with robots and how we can build the technology to meet the expectation of a flowing and natural interaction with robots. In the past decade, the social robots coming out of this research have been used in a range of applications, from education, over healthcare, to entertainment, but they always have been used in a narrow interaction context. This keynote will offer illustrative examples of the technology and robots we develop, some of the insights from our empirical work we do, and give an overview of recent applications in education and healthcare. The talk finishes on some speculation on where the new breakthroughs in AI, and specifically in Large Language Models, will take the development of social robots. Will we finally see robots that connect with people without others holding the puppeteering strings?

Biography
Tony Belpaeme is Professor at Ghent University and Visiting Professor of Cognitive Systems and Robotics at Plymouth University. His research interests include social systems, cognitive robotics, and artificial intelligence in general.
He holds a PhD from the Artificial Intelligence Laboratory at the Vrije Universiteit Brussel supervised by Luc Steels.
Tony and his team study the science and technology of human-robot interaction and cognitive robotics. Starting from the premise that intelligence is rooted in social interaction, the teams work on AI to power social robots and studies how people respond to social robots. Their theoretical work is complemented by designing and implementing robots for education and healthcare. The combination of both theoretical cognitive systems research applied to topics with societal relevance has received international recognition.

Social Signals as a Facilitator of Human-Robot Interaction

Abstract
The automatic analysis and synthesis of social signals, including voice, gestures, and facial expressions, are pivotal for the advancement of next-generation interfaces, facilitating more intuitive and natural human-computer interactions with both robots and virtual agents. During my presentation, I will introduce computational methodologies for implementing socially interactive behaviors in artificial agents, with a specific focus on three essential components: Social Perception, Socially-Aware Behavior Synthesis, and Learning Socially-Aware Behaviors. In addition to discussing analytic methods grounded in cognitive and social science theories, I will explore empirical approaches that empower artificial agents to learn socially interactive behaviors from recordings of human-human interactions or real-life engagements with human interlocutors. I will also delve into the potential and challenges arising from neural behavior generation techniques, promising to elevate virtual agents and social robots to new levels of human-likeness. Throughout the presentation, I will offer practical insights and examples drawn from our work across various application fields. To benefit users, we need to extend our focus beyond technical solutions to encompass ethical, legal, and societal considerations.

Biography
Elisabeth André is a full professor of Computer Science and Founding Chair of Human-Centered Artificial Intelligence at Augsburg University in Germany. She has a long track record in multimodal human-machine interaction, embodied conversational agents, social robotics, affective computing and social signal processing. Her work has won many awards including the Gottfried Wilhelm Leibnitz Prize 2021 of the German Research Foundation (DFG), with 2.5 Mio € the highest endowed German research award. In 2017, she was elected to the CHI Academy, an honorary group of leaders in the field of Human-Computer Interaction. To honor her achievements in bringing Artificial Intelligence techniques to Human-Computer Interaction, she was awarded a EurAI fellowship (European Coordinating Committee for Artificial Intelligence) in 2013. In 2019, she was named one of the 10 most influential figures in the history of AI in Germany by National Society for Informatics (GI). Elisabeth André is a member of the Bavarian Academy of Sciences and Humanities, the Academy of Europe, the Asia-Pacific Artificial Intelligence Association and the German Academy of Sciences Leopoldina.