PostDoc & PhD students

Amer/ Francesca/ Helen

Amer Marzuki

Amer Marzuki

Amer develops and maintains the web application that is being used by clinicians to monitor people living with dementia remotely. The web application displays important information regarding patient wellbeing, as well as generating time-sensitive alerts that may require intervention by clinicians.

Francesca Palermo

Francesca Palermo

Francesca’s primary goal is to detect episodes of agitation in people living with dementia by applying a deep learning model on in-home monitoring data. Agitation is a neuropsychiatric symptom that negatively impacts the Activities of Daily Living and independence of individuals. Detecting agitation episodes can assist in providing early and timely interventions.

Helen Lai

Helen Lai

Helen is interested in the translation of group-level data to address individual-level needs. Working with health and social care providers as well as people with dementia, she is testing the implementation of digitally-enabled care within the local community. In parallel, she is extracting trends among people with dementia in population data, using domains such as multimorbidity and frailty to predict clinical outcomes such as infections.

Martin/ Mike/ Alina

Martin Tran

Martin Tran

Martin works as part of the Synthetic Biology group, where they aim to develop novel point-of-care diagnostics for early detection of infections in people living with dementia. His role is to use molecular biology techniques to characterise the urinary microbiome and bacterial strains responsible for infections, to identify potential biomarkers for detection.

Michael David

Michael David

Michael uses detailed MRI brain scans to assess damage within patient’s noradrenaline centre. The brain chemical noradrenaline is particularly important for attention. Attention - focusing on relevant information - is often affected early in Alzheimer’s disease. Patients notice early and disabling problems with attention and concentration, which worsen memory problems.

Nan/ Alexander/ Ian

Nan Fletcher-Lloyd

Nan Fletcher-Lloyd

Nan’s research focuses on investigating the use of remote monitoring technologies to improve the provision of healthcare for people living with dementia. Through machine learning techniques and data analytics, her work looks to predict agitation risk in order to inform delivery of meaningful and timely interventions, both pharmacological and non-pharmacological.

Alexander Capstick

Alexander Capstick

Alexander’s work is focused on building machine learning models that can make clinical predictions about people’s health. Specifically, he is working on making models adaptable to changing environments and researching into how they can learn from few examples.

Tong, Ghena, Neil

Tong Wu

Tong Wu

Tong Wu has experience in telecommunication, machine learning and neuroscience. She focuses on automatic speech recognition (ASR) for language-based tests of cognition and memory for healthy populations and Dementia patients. ASR models hold promises to discover spoken biomarkers for early Dementia detection and automate cognitive speech tests in contactless manner.

Ghena Hammour

Ghena Hammour

Ghena’s research focuses on the development of Hearables, an in-ear device, for neural and physiological monitoring in patients with chronic diseases. This aims to improve patients' quality of life by providing the means for unobtrusive and continuous sensing at an affordable cost.