Rosa Hoekstra is reader in global perspectives on neurodevelopmental disorders at Kings College London in the United Kingdom.
Rosa Hoekstra
Lecturer
Kings College London
From this contributor
Remembering Zemi Yenus: An ambassador for autism in Africa
Zemi Yenus was the mother of a child with autism, founder of Ethiopia’s first school for autistic children and a tireless advocate for autism awareness and research in Africa.
Remembering Zemi Yenus: An ambassador for autism in Africa
By
Rosa Hoekstra, Andy Shih, Bethlehem Tekola, Waganesh Zeleke
15 June 2021 | 13 min read
How to address autism in Ethiopia and other low-income nations
Even short programs with a focus on mental health can train community health workers to help children with autism in Ethiopia and elsewhere.
How to address autism in Ethiopia and other low-income nations
By
Rosa Hoekstra
21 November 2017 | 8 min read
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Sharing Africa’s brain data: Q&A with Amadi Ihunwo
These data are “virtually mandatory” to advance neuroscience, says Ihunwo, a co-investigator of the Brain Research International Data Governance & Exchange (BRIDGE) initiative, which seeks to develop a global framework for sharing, using and protecting neuroscience data.
Sharing Africa’s brain data: Q&A with Amadi Ihunwo
These data are “virtually mandatory” to advance neuroscience, says Ihunwo, a co-investigator of the Brain Research International Data Governance & Exchange (BRIDGE) initiative, which seeks to develop a global framework for sharing, using and protecting neuroscience data.
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Lauren Schenkman
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Cortical structures in infants linked to future language skills; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 May.
Cortical structures in infants linked to future language skills; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 May.
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Jill Adams
20 May 2025 | 2 min read
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.
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Alona Fyshe
19 May 2025 | 7 min read