Research Assistant
El-Erian Institute of Behavioural Economics and Policy
BSc (University of Trento), MSc (University of Padua)
My research bridges data science and human-centric technology application. I developed quantitative machine learning algorithms to detect patterns in human behaviour from ambient sensor data, while integrating qualitative methods to ensure these predictive models translate into real-world impact.
I’m interested in applying Machine Learning and data analytics to the field of behavioural economics, exploring human decision-making under uncertainty.
Professional experience
Marina Vicini is a data scientist combining a rigorous quantitative background with human-centric research, holding a BSc in Mathematics from the University of Trento and an MSc in Data Science from the University of Padua.
Prior to her current position, she led an Innovate UK project, as a Knowledge Transfer Partnership Associate between Aston University and Legrand Care. She developed a proactive care solution for older adults, applying machine learning to ambient sensor data to detect behavioural anomalies, while utilising user-centred focus groups to address the systemic realities of care networks.
Her focus on socially impactful data science also led to independent consultancy engagements with Save the Children and UNICEF, stemming from a Data Science for Social Good Fellowship at the University of Warwick. This consultancy work on estimating child poverty using geospatial data grew into her MSc thesis and a published book chapter in the Handbook on Child Poverty and Inequality. Across her applied and academic roles, she maintains a deeply interdisciplinary approach, ensuring data-driven solutions translate into practical, real-world impact.
Previous appointments
Marina Vicini was a knowledge transfer associate at Aston University prior to joining Cambridge Judge Business School.
Publications
Selected publications
- Vicini, M. and Beltagui, A. (2026) “Proactive care dashboards: recommendations for ageing-in-place.” In: CHI Conference on Human Factors in Computing Systems, 13-17 April 2026, Barcelona, Spain. (DOI: 10.1145/3772363.3798908)
- Vicini, M., Rudorfer, M., Dai, Z., Beltagui, A. and Manso, L.J. (2026) “Floor plan-agnostic detection of gait speed drifts using ambient sensors.” In: International Conference on Activity and Behavior Computing (ABC) (8th), 9-12 March 2026, Hakodate, Japan. (DOI: 10.1109/ABC68169.2026.11567208)
- Vicini, M., Fitzgerald, J., Veizaga, D.P., Saggar, A. and Fiala, O. (2025) “Micro-projections of multidimensional child poverty in sub-Saharan Africa.” In: Minujin, A. and Delamonica, E. (eds.) Handbook on child poverty and inequality. Edward Elgar, pp.321-347
- Vicini, M., Rudorfer, M., Dai, Z. and Manso, L.J. (2024) “Integrating temporal context into streaming data for human activity recognition in smart home.” In: International Conference on Ubiquitous Computing and Ambient Intelligence (16th), 27-29 November 2024, Ulster University, Belfast, Northern Ireland. Cham: Springer Nature, pp.238-251 (DOI: 10.1007/978-3-031-77571-0_24)
- Vicini, M., Albut, S., Gindullina, E. and Badia, L. (2022) “Decision making via game theory for autonomous vehicles in the presence of a moving obstacle.” In: IEEE International Conference on Communication, Networks and Satellite (COMNETSAT), 3-5 November 2022, Solo, Indonesia. IEEE, pp.393-398 (DOI: 10.1109/COMNETSAT56033.2022.9994415)
Awards and honours
- Data Science for Social Good Fellowship, Warwick University, 2022