Dr Bin Chi

Bin is a data manager, working on multiple projects to provide data management and database-related support within the Academic Unit for Ageing and Stroke Research(ASR). Bin has a background in GIS and urban planning (Land Use Management), with a particular emphasis upon using statistical modelling and geographical analysis to investigate the spatio-temporal patterns of socio-economic processes to further guide local policy. Her research has focused on managing large datasets with advanced techniques to drive solutions for complex research challenges. Over the past nine years, Bin has worked with large and sensitive datasets across diverse research areas, including housing, planning, geodemographics, residential and social mobility. Now, Bin intends to continually expand her expertise to advance data-driven insights in health, especially relating aging.

Before joining ASR, she was a Senior Research Data Scientist at UCL Consumer Data Research Centre (CDRC), working in the Geospatial Analytics and Computing group within the Department of Geography. Prior to this, Bin held a postdoctoral position at the Urban Big Data Centre (UBDC) at the University of Glasgow. Before that, she did her PhD at the UCL Bartlett Centre for Advanced Spatial Analysis. During her PhD, she developed a consistent framework to coordinate and integrate analyses of linked housing data, across different spatial and temporal scales, using multilevel models (e.g. random slope model, growth curve model) to understand house prices and housing affordability variation. At the end of her PhD research she started work as a part-time Research Data Scientist/ Data Engineer in the UCL Department of Geography.

Bin enjoys expanding her data management and analysis skills to support the interdisciplinary research community, particularly with large UK-wide spatial datasets in secure data environments and high-performance computing infrastructures. For research on housing, Bin has used Ordnance Survey AddressBase Premium to geo-tag UPRN (Unique Property Reference Number) onto housing-related datasets (Land Registry Price Paid Data, Register of Scotland data, Domestic Energy Performance Certificates, Zoopla, Electoral Roll and other address- based CDRC consumer data) to advance data-driven insights in housing, geodemographics and mobility. The success of the data linkage work enabled Bin to further assist both the UCL public health team and UCL planning team to achieve high-quality UPRN tagging of their research data. Bin is a member of the interdisciplinary advisory board for the UKRI-funded project ‘Sensing On Urban Noise: Distributed Sensing for Collaborative and Sustainable Cityscapes and Living Environments (SOUNDSCALE)’.