- Paper 'Integrating Knowledge Graphs and Bayesian Networks: A Hybrid Approach for Explainable Disease Risk Prediction' accepted at the 49th IEEE International Conference on Computers, Software, and Applications (COMPSAC 2025)
- L'Oréal-UNESCO For Women In Science Young Talents Awardee
- Recipient of the Generation Google Scholarship
- Graduated with Distinction from the University of Manchester
Research Experience
- February to September 2025: Consultant at the World Bank-UNHCR Joint Data Centre on Forced Displacement as a World Bank Group Africa fellow, researching the impact of forced displacement on malaria vulnerability and burden, with a focus on how climate shocks mediate this relationship
- Coached Django Girls workshops in Nairobi, Mombasa, and Manchester
- Currently mentoring Computer Science undergraduate students as part of the KamiLimu mentorship program
Education
- PhD: Computer Science at the University of Cape Town, supervised by Prof. Deshen Moodley
- MSc: Advanced Computer Science at the University of Manchester, specializing in AI, dissertation on deep learning and human-robot interaction, supervised by Prof. Angelo Cangelosi
Background
Research Interests: AI for explainable health risk prediction and decision support, particularly using multimodal and heterogeneous health data. Integration of symbolic AI (especially ontologies and knowledge graphs) with machine learning and Bayesian networks.
Miscellany
Personal interests include: speaking, writing, and mentoring in technology; enjoys hiking, parkrun, and road tripping across the Western Cape and beyond; also enjoys listening to audiobooks or podcasts at home