Low-Burden AI Approach for Cross-National Early Identification of Cognitive Impairment Using Real-World Questionnaire Response Behaviours
Nature Communications
2026
In press
About
Biography
I am a PhD Candidate in Health Data Sciences at the University of Surrey, supervised by Dr Haomiao Jin and Dr Jenny Harris. My research develops low-burden AI and machine-learning approaches for early identification of cognitive impairment in ageing populations, using questionnaire response behaviours and other digital behavioural signals. I work with large-scale longitudinal ageing cohorts, including cross-national data from the US, England, India, Mexico and China, to examine whether behavioural signals embedded in routine survey completion can support earlier and more equitable cognitive-risk detection in community and non-clinical settings.
Postdoctoral Job Market
Thesis submission expected August 2026 · Viva expected October 2026.
Open to roles in health data science, AI for ageing & dementia, digital health, and global health methods.
Research
Interests
Machine learning & deep learning for healthcare and ageing research
Large language models, RAG & conversational AI for health and research workflows
Digital biomarkers & behavioural signals from real-world data
Cross-national and global health data science
Projects
Research Projects
2023 — 2026
Testing Early Markers of Cognitive Decline and Dementia Derived from Survey Response Behaviors
Researcher · NIH/NIA-funded Subaward (R01AG068190)
International collaboration between the University of Surrey and the University of Southern California. University of Surrey PI: Dr Haomiao Jin; Project PI: Professor Stefan Schneider (USC Leonard Davis School of Gerontology).
Publications
Selected Papers
First-author publications
Early identification of cognitive impairment in older adults from Advanced Activities of Daily Living (AADL): A scoping review
Public Health · 246, 105822
2025
Early identification of cognitive impairment in community environments through modeling subtle inconsistencies in questionnaire responses
JMIR Formative Research · 8, e54335
2024
A hybrid ConvLSTM-based anomaly detection approach for combating energy theft
IEEE Transactions on Instrumentation and Measurement · 71, 1—10
2022
67 citations
Co-authored publications
Strain and recovery activities over a week predict short-term changes in processing speed measured in everyday environments
Neuropsychology · Advance online publication
2026
Dementia ascertainment in India and development of nation-specific cutoffs: A machine learning and diagnostic analysis
Alzheimer's & Dementia: DADM · 17(1), e70049
2025
Evidence Supports the Validity and Reliability of Response Times from a Brief Survey as a Digital Biomarker for Processing Speed
American Journal of Epidemiology
2025
Can you tell people's cognitive ability level from their response patterns in questionnaires?
Behavior Research Methods · 56(7), 6741—6758
2024
Attrition from longitudinal ageing studies and performance across domains of cognitive functioning: an IPD meta-analysis
BMJ Open · 14(3), e079241
2024
Experience
Research Experience
2023 — present
PhD Candidate
University of Surrey, UK
Machine-learning approaches using cross-national ageing cohort data to identify early risk of cognitive impairment from questionnaire response behaviours. Collaboration with USC on an NIH-funded interdisciplinary project. Contributed to the design of an AI-enabled survey platform for patient-reported outcomes.
Jun — Jul 2024
Research Officer
Henley Business School, University of Reading, UK
Analysed large-scale census data using statistical and machine-learning methods; developed geospatial visualisations for applied research.
Dec 2022 — Mar 2023
Research Associate
Henley Business School, University of Reading, UK
UKRI AKT2I programme. Applied AI for sentiment analysis and text mining on real-world datasets with academic and industry partners.
Education
Academic Background
2023 — present
PhD in Health Sciences
University of Surrey, UK
Thesis: Developing Machine Learning Tools for Predicting Cognitive Impairment from Survey Response Behaviours.
Funded by the University of Surrey Faculty of Health and Medical Sciences Doctoral Studentship (PGR scholarship).
2020 — 2021
MSc Information Security (Distinction)
Royal Holloway, University of London, UK
Skills
Technical Expertise
ML & AI
Predictive modelling, deep learning (TensorFlow, PyTorch), explainable AI
Large Language Models
Prompt engineering, embedding models, RAG, conversational AI applications
Statistical Methods
Item response theory, psychometric analysis, advanced statistical modelling in R
Engineering
Full-stack development, interactive research tools, rapid prototyping with Streamlit
Recognition
Awards & Presentations
2026
Oral Presentation
International Association of Gerontology and Geriatrics Congress
2025
Stirling Award Commendation
Best Student Poster, British Society of Gerontology
2024
Oral Presentation
Gerontological Society of America Annual Scientific Meeting
2024
Oral Presentation
British Society of Gerontology Annual Conference
2023
Faculty of Health and Medical Sciences Doctoral Studentship
University of Surrey · Competitive PGR scholarship (fully funded)
2022
Computer Weekly Search Security Awards
Royal Holloway, University of London
Service
Academic Service
Peer reviewer for npj Aging, npj Digital Medicine, BMC Public Health, Scientific Reports.