Elise Robinson is an institute member at the Broad Institute of MIT and Harvard in Cambridge, Massachusetts.
Elise Robinson
Institute member
Broad Institute of MIT and Harvard
From this contributor
What developmental milestones say about autism research: A conversation with Susan Kuo and Elise Robinson
Shifts in diagnostic criteria have only added to the condition’s bedeviling heterogeneity, an analysis of smiling, sitting, walking and other early milestones in more than 17,000 autistic children reveals.
What developmental milestones say about autism research: A conversation with Susan Kuo and Elise Robinson
By
Sarah DeWeerdt
10 August 2022 | 7 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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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