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Estimating global migration flows by combining traditional and innovative data sources using machine learning

By using machine learning, this research project combines multiple innovative data sources such as Google search and air traffic data with traditional migration statistics to estimate global migration flows
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Understanding public attitudes towards refugees with radio content analysis

Analysing public radio content in Uganda using speech-to-text technology to understand attitudes towards refugees
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Automated analyses of satellite and sensor imagery: Supporting operations during humanitarian emergencies by detecting geographic structures, using machine learning

Using machine learning for detecting geographic structures and estimating displaced populations in humanitarian emergencies
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GeoMatch: Using artificial intelligence to improve refugee integration through data-driven assignments

Allocating refugees to optimal resettlement locations for integration success in the United States and Switzerland

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