Background
MSc Artificial Intelligence & Machine Learning; BSc Computer Science
PhD
Weather, Vector-Borne Diseases & Resilience in BrazilMy project predicts how climate variability and extreme weather events influence the spread of vector-borne diseases in Brazil. It sits at the intersection of climate science, public health, and artificial intelligence, with the aim of developing a Dengue forecasting system.
I integrate national health records (SINAN), satellite-based Earth observations, and seasonal weather forecasts to build a dataset which is used to train range of models, including Bayesian approaches, Gaussian neural networks, Long Short-Term Memory (LSTM) networks, and ensemble methods, to capture uncertainty and complex temporal patterns. The overarching goal is to improve accuracy and increase forecast lead times.
Supervisors
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Lead Supervisor
Theo Economou
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Co-Supervisor
Scott Hosking
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Co-Supervisor
Hywel T.P. Williams
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Co-Supervisor
Alejandro Coca Castro
External Partners
- Leo Bastos - Programa de Computação Científica (PROCC), Fundação Oswaldo Cruz, Rio de Janeiro, Brazil