I am a statistical scientist specialising in spatial and spatio-temporal modelling for global health, with a particular focus on neglected tropical diseases and other health challenges in low-resource settings. My research develops geostatistical methods to improve disease surveillance, map burden, and support programmatic decision-making. I have led several internationally funded projects as Principal Investigator and collaborate with global partners to ensure that statistical innovation informs real-world health policy.

I have created and delivered MSc-level modules in statistical modelling and epidemiology, and I have developed and taught international training courses in model-based geostatistics for diverse audiences, including health professionals and academic researchers. I take a research-led and inclusive approach to teaching, integrating practical applications and reproducible tools to support students from a wide range of academic and professional backgrounds.

I supervise MSc, PhD students and postdoctoral researchers across interdisciplinary areas in spatial statistics and disease mapping. I tailor my mentoring style to foster independence and critical thinking, and I am committed to inclusive and supportive supervision. My work reflects a broader commitment to capacity building, equity in global health, and the role of statistical science in advancing evidence-based policy.

• Spatial and spatio-temporal statistics for global health.
• Mapping and modelling neglected tropical diseases.
• Survey design and surveyllance systems.
• Open-source statistical software and capacity building.