Zachary J. Williams
M.D./Ph.D. student
Vanderbilt University
From this contributor
Designing autism-friendly trials: Q&A with Caroline Averius and Zachary Williams
The pair’s new guidebook offers practical steps to make clinical trials easier and more meaningful for autistic participants.
Designing autism-friendly trials: Q&A with Caroline Averius and Zachary Williams
A new hub for participatory research: Q&A with Zachary Williams
Last month, the International Society for Autism Research launched the INSAR Community Collaborator Request (ICCR), an online forum to foster collaborations between autistic people and autism researchers. Its creator, Zachary Williams, explains how researchers can make the most of this new resource.
A new hub for participatory research: Q&A with Zachary Williams
Measuring alexithymia in autistic people
Despite the growing interest in alexithymia in autism research, the tools commonly used to measure this trait may not work reliably in autistic populations. A new scoring method fills that gap.
Measuring alexithymia in autistic people
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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.
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.
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.