Physiological responses to stimuli can reveal personality traits
Professor Shlomo Berkovsky, computer scientist and research leader at Macquarie University, will give a workshop on technology for detecting personality traits.
The workshop, titled “Personality Sensing: Detection of Personality Traits Using Physiological Responses to Image and Video Stimuli”, introduces a framework for objective personality detection that replaces lengthy self-report questionnaires with physiological responses to affective image and video stimuli. With non-invasive eye-tracking and sensors for skin conductivity, the subjects’ responses are processed using machine learning methods to predict their personality traits. The research highlights which traits can be most accurately detected, the relative importance of different stimuli and signals, and the potential applications in psychology, healthcare, and personalised interactive systems.
Professor Shlomo Berkovsky's presentation will take place on 26 August at 10:15 in room BESK, Forskningsgången 6, Gothenburg with the possibility to participate via Zoom. It is part of the workshop "Digital workshop: hur AI formar vår vardagliga hälsa", linked to below.
Shlomo Berkovsky is a computer scientist, with theoretical and applied expertise in areas related to human-centric application of AI. His original research areas include user modeling and personalised technologies and he currently leads the Clinical AI and Sensing Technologies stream at the Centre for Health Informatics at Macquarie University. The stream focuses on the use of AI methods to develop personalised predictions of diagnosis and care, and studies how sensors can be deployed to predict medical conditions, and how clinicians interact with health technologies. He has a sustained record of research leadership, evidenced by publications at top outlets, editorship of ACM Transactions on Interactive Intelligent Systems, conference best paper awards, keynote talks and tutorials, sustained research funding stream, and leading research programmes.
For those interested in meeting with Professor Berkovsky in connection with the workshop, please contact Alan Said.
