Emily Laber-Warren heads the health and science reporting program at the Craig Newmark Graduate School of Journalism at the City University of New York. She has been a staff editor at Popular Science, The Sciences, Scientific American Mind, and Women’s Health.
Emily Laber-Warren
From this contributor
Shafali Jeste: Early autism meets its match
Shafali Jeste has spent the bulk of her scientific career searching for biological markers of autism. Her goal: to improve lives through early diagnosis and speedy testing of therapies.
Shafali Jeste: Early autism meets its match
By
Emily Laber-Warren
30 November 2021 | 11 min read
The benefits of special interests in autism
Researchers are studying how the intense passions of autistic people shape the brain, improve well-being and enhance learning.
The benefits of special interests in autism
By
Emily Laber-Warren
12 May 2021 | 18 min read
How autism shapes sibling relationships
Having an autistic brother or sister can pose challenges, but it can also make children patient, empathetic and resilient.
Explore more from The Transmitter
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.
By
Lauren Schenkman
20 May 2025 | 6 min read
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.
By
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.
By
Alona Fyshe
19 May 2025 | 7 min read