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Keynote speaker: Dr Maggie Aderin-Pocock MBE
"Engineering the Universe"
Dr Andrea Giusti
"Electromagnetic control of engineered fluids: Towards a paradigm shift in aircraft propulsion"
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ENERGY room
Dr Niall Kirkaldy
"Understanding the usage-dependent degradation of lithium-ion batteries"
ENERGY room
Farron Hesse
"Bimodal wake dynamics of squareback bluff-bodies: a journey from academia to industry application"
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ENERGY room
Dr Richard Williams
"Creep deformation and residual stress relaxation in Additively Manufactured Stainless Steel 316L"
MATERIALS & STRUCTURES room
Chenpeng Tong
"An energy-saving hot stamping process for the production of ultra-high-strength lightweight structural components"
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MATERIALS & STRUCTURES room
Sebastian Larsen
"Machine learning for defect detection in metal 3D printing"
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MACHINE LEARNING room
Dr Maitreyee Wairagkar
"Affective Conversational Robots with Machine Learning for Dementia Care"
Social robots are anthropomorphised platforms developed to interact with humans, using natural language, offering an accessible and intuitive interface suited to diverse cognitive abilities. Social robots can be used to support people with dementia in their homes and monitor their wellbeing and health. Such robots have the potential to reduce care burden and prolong independent living, yet their practical translation remains insignificant. We have developed conversational social robots capable of communicating through natural language and facial expressions using conversational AI to improve engagement with people with dementia. We record user interactions with these robots to automatically assess their health and wellbeing using machine learning models. We use natural language processing to analyse conversations and identify topics of interest such that robot behaviour could be tailored to individuals. We process speech using signal processing and machine learning classifiers to identify emotions and mood. These social robot applications can support people with dementia and carers at home and also help clinicians monitor their patients remotely. Affective social robots with voice and facial expressions thus have a great potential for enhancing dementia care.
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MACHINE LEARNING room
PhD study
Early Career Research Fellowships
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