Select Work
︎Causal ML for Syndemic Risk Quantification and Intervention Impact Forecasting
Leading a federally funded study applying machine learning and causal methods to EHR data from over 8 million patients across Federally Qualified Health Centers. Identifying syndemic risk clusters and estimating intervention effects for cardiometabolic disease in underserved populations. (Code and preprint forthcoming)
︎ NLP Applications for Public Health in Africa
Co-led a systematic scoping review mapping natural language processing applications across African health systems, identifying evidence gaps and opportunities for AI deployment in low-resource contexts.
︎ Sentiment Analysis of Preventive Behaviors During COVID-19
Analyzed social media engagement patterns around non-communicable disease prevention behaviors during lockdowns in Nigeria, generating insights on maintaining prevention messaging during public health emergencies.
︎ Mapping Health Resource Access Using Crowdsourced Data
Used crowdsourced digital platform data to map the relationship between neighbourhood deprivation indices and availability of health-promoting resources across Canadian cities — an early application of non-traditional data sources to understand spatial inequities in health resource access.
︎ Evidence & Gap Map — Inclusive Interventions for Children with Disabilities
Led production of a global evidence and gap map systematically mapping interventions for children with disabilities across low- and middle-income countries, informing UNICEF's Global Research Agenda and strategic investment priorities.