Human Robot Interaction and Agentic AI for Assistive Living

About the Project

Approximately one million people in the UK live with dementia, and the risk rises sharply after the age of 80. Dementia is one of the most urgent challenges in health and computing research, and Robotics and AI is beginning to transform how we respond to it. This PhD will advance us towards a future in which Human Robot Interaction (HRI) plays a continuous and proactive role throughout dementia care.

One of the most pressing and underexplored areas is helping people who are already at elevated risk, or in the early stages of dementia, to remain in their own homes for longer. With a particular focus on adults aged 80 and above, the PhD student will co-design, build, and evaluate a system combining a socially assistive robot with agentic AI.

The project will explore research questions including how HRI and agentic AI can be designed to delay cognitive decline through personalised engagement and stimulation at home, and how they can provide effective compensatory support and life assistance to help older adults maintain independence at home.

The successful PhD candidate will explore agentic AI, for example multi-modal reasoning, integrating speech, vision, and sensor data. HRI addresses how older adults engage naturally and trustingly with a robot in their own home. The work will produce a co-design framework for trustworthy human-robot interaction with cognitively vulnerable adults, a tested prototype, and feasibility evidence.

You will be supervised by Professor Lynne Baillie and Dr Yingfang Yuan.

Eligibility Requirements

• Academic excellence i.e. 2:1 (or equivalent GPA from non-UK universities with preference for 1st class honours); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
• Appropriate IELTS score, if required.
• Applicants cannot apply if they are already a PhD holder or if currently engaged in Doctoral study at Northumbria or elsewhere.
• Must be able to commit to campus-based full-time or part-time study.