Research
We specialize in a wide range of ML approaches including time series forecast, causal inference, ensemble learning, reinforcement learning, deep learning and survival analysis.
Our research focuses on machine learning methods with the goal of improving engagement in global health
Research collaborations
Publications
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Midwifery Learning and Forecasting: Predicting Content Demand with User-Generated Logs
A Recommendation System to Enhance Midwives' Capacities in Low-Income Countries
