Lecturer in Predictive Analytics
Antonia is a Lecturer in Predictive Analytics. Before joining the MSBE group at the University of Edinburgh Business School, she was a Postdoctoral Research Associate at Carnegie Mellon University within the Pittsburgh Supercomputing Center, researching synthetic populations and multi-dataset integration therein. She holds an MSc in Marketing & Business Analysis and a PhD from the University of Edinburgh.
Antonia's research covers multiple issues around social science and policy making, and their intersection with computational statistics and machine learning. She has a strong interest in directly working with policy makers, local organisations and grassroot movements. Currently, she is investigating financial wellness and relating it to geospatial inequality and the wider wellbeing of a person, as well as food systems and local access to healthy food. Her current methodological research question relates to how dissimilarities between data from multiple sources are calculated in different contexts, stemming from her work on segmentation and clustering approaches.
Topics for PhD supervisions are ML applications in the social sciences / computational social sciences, which include but are not limited to:
- marketing and consumer behaviour (through, for example, predictive modelling and segmentation approaches),
- tourism and travel movement (through, for example, spatio-temporal analysis),
- financial wellbeing and mental/physical population health (through, for example, synthetic populations and the analysis of cohort/survey data within them),
- spatial inequality in all of the above.