Antonia Gieschen

Dr. Antonia Gieschen is a Lecturer in Predictive Analytics at the University of Edinburgh Business School, where she leads undergraduate cohorts in Business and Economics (2025–current) and organizes the MSBE Research Seminar Series. She teaches courses including Principles of Data Analytics and Predictive Analytics and Modelling of Data, with office hours dedicated to both undergraduate and postgraduate students.

• Education:
  • MSc in Marketing & Business Analysis
  • PhD from the University of Edinburgh

Her research focuses on the intersection of Machine Learning, Computational Statistics, and Social Science, aiming to address policy challenges through data-driven insights. Key areas include Financial Wellness, Geospatial Inequality, and Food Systems, with a methodological emphasis on clustering algorithms, synthetic population modeling, and multi-dataset integration. She supervises PhD students interested in ML applications in social sciences, such as financial well-being, consumer behavior, and spatial inequality.

Her recent publications highlight the development of SynthEco, an open-source Python tool for creating multi-scale digital ecosystems anchored in synthetic populations. This work spans geospatial clustering in urban retail environments, temporal analysis of behavioral data, and multi-layered surveillance for food environments and public health. Themes across her research include data integration, privacy concerns, and clustering approaches, reflecting her focus on translating computational methods into actionable policy insights.

Antonia actively collaborates with institutions like the Pittsburgh Supercomputing Center at Carnegie Mellon University and Wageningen University & Research, presenting her work at international conferences including PEARC '25, ISPRS, and IEEE Big Data. She integrates synthetic populations with real-world datasets to analyze complex human behaviors, advocating for interdisciplinary engagement with policymakers and grassroots organizations.