I attempt to develop new methods of mapping natural hazard social vulnerability in developing countries. Where “social vulnerability” refers to the well-established phenomenon that people of certain social groups are more negatively affected by natural hazards. With regards to informal settlements official statistics such as census data are typically lacking and surveys are expensive and difficult to collect. As a result, my research attempts to use sources of data from in particular remote sensing to map social vulnerability, such as brightness at night and information derived from visible light satellite imagery.
pathway: Advanced Quantitative Methods Alumni
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Dr Alex Kwong
Both genes and the environment contribute to psychiatric disorders, however the extent to which they both contribute and interact to cause illness is still poorly understood. Modelling longitudinal data is one way to explore this relationship. My research uses data from the Avon Longitudinal Study of Parents and Children (ALSPAC) and statistical techniques such as multilevel modelling (MLM) to address this topic.
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Dr Tim Morris
My research employs longitudinal cohort modelling to examine the way in which key life events such as residential mobility in childhood and adolescence impact upon health and educational outcomes in these periods. My research is situated in an advanced quantitative framework and principally conducted on the Avon Longitudinal Study of Parents and Children, a Bristol based cohort of children born in the early 1990’s, and draws on elements from the epidemiological, educational, geographical, and broad social science disciplines.
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Dr Beatriz Gallo Cordoba
My research concerns the link between ethnicity and pupils’ attainment. In particular, the research employs multilevel modelling to understand the link between ethnic segregation and ethnic attainment gaps at the end of compulsory education in Colombia.
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Dr Satpal Singh Sandhu
My research involves adaptation and development of Advanced Quantitative Methods for modelling complex longitudinal craniofacial growth data. The objective is to advance understanding of craniofacial growth process (primary focus would be face) from early childhood through to adulthood. My research is based on the data collected from various historic longitudinal growth studies conducted in the 20th Century and presently part of American Association of Foundation Legacy (AAOFL) collection database.

