I contribute to research that aims to understand how we can use large data systems to understand drivers of micronutrient undernutrition through mathematical modelling. My research questions how national and global nutrition stakeholders can generate subnational insights into diets across populations from large open-source survey data and how these data can be used to predict the contributions of large micronutrient interventions for populations in need.

I hold a dual role at the UN World Food Programme and with the Nutrition Group at the London School, where my time is split between two main projects. The first is called the Modelling & Mapping Inadequate Micronutrient Intake (MIMI) project, which aims to fill data gaps for micronutrient policy and programme planning by using both statistical and predictive modelling. The second is called the Micronutrient Action Policy Support (MAPS) project which aims to develop a co-designed, web-hosted tool to model estimates of micronutrient deficiencies at sub-national scales and explore pathways to improve nutrition.

I also work as a technical consultant on topics related to public health nutrition data, with prior experiences working for Epicentre, Médecins Sans Frontières, USAID, UNICEF, and Stanford University. I strongly value understanding the contexts behind the data that I analyse and have experiences working in Democratic Republic of the Congo, Niger, Ethiopia, and Malawi. I was a Peace Corps volunteer in Cameroon, hold a PhD and MSc from the London School, and a B.S. in Environmental Science from UCLA.

In my free time, I enjoy hiking, camping, cooking, and skateboarding.