Rebeca Moreno Jimenez
Dados Biográficos
| ID | 9798182 |
|---|---|
| NOME | Rebeca Moreno Jimenez |
| PRENOMES | Rebeca Moreno |
| SOBRENOME | Jimenez |
| ASSINATURA | JIMENEZ R M |
| AFILIAÇÕES | Office of the United Nations High Commissioner for Refugees |
| ORCID | 0000-0003-0864-5594 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 2 |
| TOTAL DE CITAÇÕES | 0 |
| TOTAL COMO AUTOR | 2 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2021 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2022 |
| ÍNDICE H | 0 |
Epidemiological modelling in refugee and internally displaced people settlements
The spread of infectious diseases such as COVID-19 presents many challenges to healthcare systems and infrastructures across the world, exacerbating inequalities and leaving the world’s most vulnerable populations at risk. Epidemiological modelling is vital to guiding evidence-informed or data-driven decision making. In forced displacement contexts, and in particular refugee and internally displaced people (IDP) settlements, it meets several chal…
Explicability of humanitarian AI
In the debate on how to improve efficiencies in the humanitarian sector and better meet people’s needs, the argument for the use of artificial intelligence (AI) and automated decision-making (ADMs) systems has gained significant traction and ignited controversy for its ethical and human rights-related implications. Setting aside the implications of introducing unmanned and automated systems in warfare, we focus instead on the impact of the adopti…
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Explicability of humanitarian AI
In the debate on how to improve efficiencies in the humanitarian sector and better meet people’s needs, the argument for the use of artificial intelligence (AI) and automated decision-making (ADMs) systems has gained significant traction and ignited controversy for its ethical and human rights-related implications. Setting aside the implications of introducing unmanned and automated systems in warfare, we focus instead on the impact of the adopti…
Epidemiological modelling in refugee and internally displaced people settlements
The spread of infectious diseases such as COVID-19 presents many challenges to healthcare systems and infrastructures across the world, exacerbating inequalities and leaving the world’s most vulnerable populations at risk. Epidemiological modelling is vital to guiding evidence-informed or data-driven decision making. In forced displacement contexts, and in particular refugee and internally displaced people (IDP) settlements, it meets several chal…
Engineering (2 obras) · Management science (2 obras) · Political science (2 obras) · Accountability (1 obras) · Adversarial Robustness in Machine Learning (1 obras) · Artificial Intelligence in Healthcare and Education (1 obras) · Computer Science (1 obras) · COVID-19 epidemiological studies (1 obras) · Disaster Response and Management (1 obras) · Disease (1 obras)