SOURCE-LINKED INTELLIGENCE
Spatial machine-learning analysis of child indicators
plines: child development, spatial analysis of satellite images, and machine-learning. Satellite images and households’ simulations will complement the missing or outdated information of surveys, and machine learning will identify children that could be left behind during the development process due to the intersectionality of gender with biological diversities, ethnicity, socio-economic status, and geographical location. The project will create new tools for monitoring the progress towards the SDGs and will help to formulate targeted interventions that increase the social impact and reduce the economic costs of poverty-reduction and development programs. If the project is funded, Dr. Rolando Gonzales Martinez will carry out the fellowship at the University of Groningen, under the supervision of Prof. Dr. Hinke Haisma and with support from Prof. Dr. Dimitris Ballas. A short visit to UNICEF is planned as a secondment for Dr. Gonzales Martinez, so he can work with UNICEF on improving the policy impact of the project. The transfer of knowledge between the research fellow and the host or
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 203464.32
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T01:21:06.728Z. This is not the publication date.