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Human-Robot Interaction
Machine Learning with Application to Robotics
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Computational Neuroscience and Cognitive Modeling

Computational Neuroscience and Cognitive Modeling

Artificial agents which learn through imitation and social interactions provide important insights for human social cognition. We focus on modelling the cognitive mechanisms involved in social interaction, such as intention attribution and agency. Our research enables us to design human-like robotic behaviors to reach more realistic human-robot interactions.


We develop approaches and applications:
  • propose developmental models to explain social impairments related to schizophrenia
  • model and understand social and interactive behavior using robotic platforms and computational models
  • Social and Therapeutic Robotics

    Social robots are a promising tool to provide therapeutic frameworks for individuals with social impairments such as autism and schizophrenia. In collaboration with psychiatrists specialized in social impairments, we focus on researching and providing impairment-specific social behaviors for robots.

    We develop approaches and applications:
  • use the iCub to contrast the effect of social (human-like) and non-social (computer-displayed) feedback on schizophrenic patients
  • develop and test an innovative rehabilitation method to improve relational deficits by
  • use humanoid robotics and virtual reality
  • Related publications