Meet the keynotes of our conference!


Professor at Swiss Federal Institute of Technology Zurich

Professor Emily Cross

Perspectives on Social Robots Supporting (Mental) Health

Most people’s experience with social robots (defined as robots designed to engage and interact with humans in complex social contexts) comes from science fiction, where we encounter these machines doing everything from conversing with human companions and assisting with daily life to performing super-human tasks and saving the world.

While advances in real-world social robotics have yet to produce machines that are quite as capable as those conjured up on our novel pages and cinema screens, we are nonetheless witnessing rapid progress in the development and deployment of robots to assist humans in social contexts.

One place where this progress is particularly pronounced is in healthcare. Social robots are being equipped with technologies such as sensors, cameras, microphones, and processors which facilitate the high-fidelity collection of human data like position, gaze, speech, emotions, and feelings, and can be used to support real-time analysis of human interaction behaviour. Moreover, recent work demonstrates how interventions deploying social robots can simulate social behaviour and trigger emotions and feelings from human users, thus assisting with mental health.

Therefore, as the health psychology research field aims to understand the interplay of psychological, social, behavioural, biological and cultural factors on human health and well-being, human-robot interaction (HRI) research provides unique opportunities for studying how social robots may positively impact human health and well-being.

In this talk, I will address several avenues for the introduction of social robots in health psychology settings, with a focus on my team’s work exploring these robots’ potential in mental health support.

Professor at Clinical Data Science Maastricht

Professor André Dekker

Artificial Intelligence in healthcare

Artificial intelligence will have a major impact on day-to-day healthcare practice with the first AI products widely available. In this key note the rationale for AI in healthcare is first presented. Then the importance of data for AI is stressed but access to sufficient data is hampered by many ethical and privacy concerns. Methods to develop and validate AI including a number of trends in this field are shown. Finally, applications of two main types of AI are presented – those that lead to more efficiency and those that lead to higher efficacy.

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