Summary
I am a postdoctoral Research Associate in Geospatial Data Analytics at the UK Small Area Health Statistics Unit (SAHSU), part of the MRC Centre for Environment and Health.
My research interests primarily encompass two key areas: 1) the study of geodemographics and its applications within the GeoHealth domain, and 2) the implementation of GeoAI and the analysis of multi-sourced spatiotemporal (big) data in urban analytics, specifically in relation to public health. At present, my work is predominantly focused on investigating the disparities in air pollution dynamics across various geodemographic groups within the UK.
Before joining Imperial College London, I completed my postdoctoral research at the Martin School, University of Oxford, where I employed Google Street View imagery to extract urban perceptions and examined their potential applications in health disparities. Additionally, I was involved as a Postdoctoral Researcher in the 'Virus Watch' project at University College London, which entailed the analysis of the COVID-19 pandemic and its associated government responses in relation to human mobility (derived from massive smartphone GPS data).
I obtained my PhD in Geographic Data Science from the Geographic Data Science Lab (GDSL) at the University of Liverpool. Furthermore, I hold an MSc in Geographic Information Sciences from University College London, as well as a BA in Environment & Urban Planning from the University of Liverpool.
Selected Publications
Journal Articles
Liu Y, Chen M, Wang M, et al. , 2023, An interpretable machine learning framework for measuring urban perceptions from panoramic street view images, Iscience, Vol:26, ISSN:2589-0042
Nguyen V, Liu Y, Mumford R, et al. , 2023, Tracking Changes in Mobility Before and After the First SARS-CoV-2 Vaccination Using Global Positioning System Data in England and Wales (Virus Watch): Prospective Observational Community Cohort Study, Jmir Public Health and Surveillance, Vol:9, ISSN:2369-2960
Cheng T, Chen T, Liu Y, et al. , 2022, Human mobility variations in response to restriction policies during the COVID-19 pandemic: An analysis from the Virus Watch community cohort in England, UK, Frontiers in Public Health, Vol:10
Chen M, Liu Y, Arribas-Bel D, et al. , 2022, Assessing the value of user-generated images of urban surroundings for house price estimation, Landscape and Urban Planning, Vol:226, ISSN:0169-2046, Pages:104486-104486
Fisher T, Gibson H, Liu Y, et al. , 2022, Uncertainty-Aware Interpretable Deep Learning for Slum Mapping and Monitoring, Remote Sensing, Vol:14
Cheng T, Liu J, Liu Y, et al. , 2022, Measures to prevent nosocomial transmissions of COVID-19 based on interpersonal contact data, Primary Health Care Research & Development, Vol:23, ISSN:1463-4236
Cheng T, Lu T, Liu Y, et al. , 2021, Revealing spatiotemporal transmission patterns and stages of COVID-19 in China using individual patients’ trajectory data, Computational Urban Science, Vol:1
Byrne T, Patel P, Shrotri M, et al. , 2021, Trends, patterns and psychological influences on COVID-19 vaccination intention: Findings from a large prospective community cohort study in England and Wales (Virus Watch), Vaccine, Vol:39, ISSN:0264-410X, Pages:7108-7116
Liu Y, Singleton A, Arribas-bel D, et al. , 2021, Identifying and understanding road-constrained areas of interest (AOIs) through spatiotemporal taxi GPS data: A case study in New York City, Computers Environment and Urban Systems, Vol:86, ISSN:0198-9715, Pages:101592-101592
Hayward A, Fragaszy E, Kovar J, et al. , 2021, Risk factors, symptom reporting, healthcare-seeking behaviour and adherence to public health guidance: protocol for Virus Watch, a prospective community cohort study, Bmj Open, Vol:11, ISSN:2044-6055
Liu Y, Cheng T, 2020, Understanding public transit patterns with open geodemographics to facilitate public transport planning, Transportmetrica A: Transport Science, Vol:16, ISSN:2324-9935, Pages:76-103
Liu Y, Singleton A, Arribas-Bel D, 2020, Considering context and dynamics: A classification of transit-orientated development for New York City, Journal of Transport Geography, Vol:85, ISSN:0966-6923, Pages:102711-102711
Liu Y, Singleton A, Arribas-Bel D, 2019, A Principal Component Analysis (PCA)-based framework for automated variable selection in geodemographic classification, Geo-spatial Information Science, Vol:22, ISSN:1009-5020, Pages:251-264