Invited Speakers

Speaker-Bio: He received the Laurea (cum laude) and PhD degrees in computer engineering from the University of Catania, Italy, in 2005 and 2009, respectively. He is Fellow of the HEA and Senior Member of the IEEE.

His research specialises in computational intelligence and its application to cognitive modelling, human-robot interaction, computer-aided assessment of intellectual disabilities, and embedded computer systems.

Improvement of interaction quality in Socially Assistive Robotics can be stimulated by novel artificial intelligence algorithms. This is one of the applications of Cognitive Robotics, which is a multi-disciplinary research area that connects robotics, cognitive science and artificial intelligence, and often applies models based on biological cognition. The effort is to exploit the principles of embodied cognition, in which the body is a crucial component of the cognitive process, for the creation of more intelligent robots with human-like abilities and interaction performance. Indeed, cognitive robots capable of social interaction may provide individualised assistance to some classes of people (e.g. children with autism or elderly with cognitive decline) while exploiting the computational intelligence for data collection and processing.

The talk will present significant results of several research projects to provide an overview of the current state-of-the-art in the area of cognitive robotics, increase the awareness of benefits and limitation, and discuss the potential breakthroughs and implications for professionals in several disciplines. The talk will also emphasise responsible user-centred research to empower people rather than substitute them.

Speaker-Bio: Maartje de Graaf is an Assistant Professor of Information and Computing Sciences at Utrecht University, The Netherlands. Her research focuses on peoples social, emotional, and cognitive responses to robots aiming for the development of socially acceptable robots that benefit society. She is Associate Editor of Transactions on Human-Robot Interaction, At Large member of the HRI Steering Committee, part of the Organizing Committee of HRI 2020, and served as social science expert at the IEEE Standards Association. She has been awarded as HRI Pioneers in 2014, 25 Women in Robotics (by robohub.org in 2017), and Inspiring Fifty Netherlands (by Inspiring Fifty in 2019).

Despite the technological advancements of social robotics, long-term user acceptance of these systems remains a challenge. My research has shown that users undergo several stages of experiences when deciding (not) to (continue to) use the robots we have developed. At each stage, users have different experiences resulting in different factors under consideration in their decision for adoption or continued use. Based on my long-term home studies deploying 70 robots for over 6 months, I have developed a phased framework of long-term social robot acceptance. In this talk, I will discuss the six phases in detail and highlight the relevant user experiences and acceptance factors affecting social robot acceptance at each stage. This knowledge reveals how we can improve human-robot interaction at each phase and increase long-term social acceptance of our robot systems.

Speaker-Bio : Her research bridges the fields of brain-computer interfaces, robotics, and cognitive science by developing adaptive BCI systems that enhance the human-machine interaction and increase the human cognitive capacities. In the past, she focused on the sense of embodiment that operators experienced during BCI-operation of a humanlike robot and introduced a new neurofeedback training paradigm that could improve their learning of a motor imagery task. Currently, she is working on the development of BCI-controlled robots/avatars that monitor users' brain activity in real time and perform a user-specific therapeutic intervention.

Social robots are emerging technologies that promise opportunities for an effective interaction with humans particularly in the healthcare and educational settings. For realization of a socially successful interaction in each of these domains, the robot needs to be able to estimate user's mental and emotional states and respond to them in an adaptive user-centered design. This talk intends to present current advances in the objective evaluation of HRI through neurophysiological measures of brain activity. We will discuss the opportunities provided by EEG-based affective computing and passive neurofeedback of user's states in robot-meditated therapy.

Speaker-Bio: She has over 18 years of teaching and research experience working on externally funded projects with partners from a diverse range of commercial and industrial enterprise. Her multi-disciplinary background, underpinned by degrees in Electronic Systems Engineering, Biomedical Instrumentation Engineering and a PhD in Computer Science, enable her to address technical issues from a soft systems perspective in relation to human experience of technology in different contexts. Her current portfolio of projects includes assistive robotics technology to support older adults with ageing-related impairments, intelligent data processing for smart home sensing, sensor systems for understanding children's use of powered mobility and adaptive interfaces for driverless cars.

The development of socially and physically assistive robots to support people with ageing-related impairments to live independently for as long as possible, continues to grow as an active area of research. Ageing can cause increased frailty, but also sensory and cognitive impairments. These impairments can result in a range of accessibility issues affecting the quality of human-robot interaction. In addition, given that the severity of ageing-related impairments can change over time, a system that was once effective, could gradually become unsuitable due to progressive decline of the person’s condition. In this talk, I will discuss the challenges in ensuring effective interaction when people have accessibility needs, in particular the impact these can have on safety and the quality of user experience, and how we can adapt our design and evaluation approaches to ensure that accessibility needs are considered from the early stages of system design.