Elissa Ball is a former data analysis intern for Spectrum. Prior to coming here, she worked in the Yonkers Public Library and as a tutor for Kaplan Test Prep. She earned a bachelor’s degree in anthropology, with a minor in mechanical engineering, from the University of Pennsylvania, in Philadelphia.
Elissa Ball
From this contributor
Why autism training for police isn’t enough
Inconsistent and underfunded training programs may hurt more than they help, experts say.
Why autism training for police isn’t enough
By
Elissa Ball, Jaclyn Jeffrey-Wilensky
26 November 2020 | 16 min read
Autistic and non-autistic youth get different healthcare as they age
Young people with autism receive more mental health services, more consistent primary care and less gynecological or urgent care than their neurotypical peers.
Autistic and non-autistic youth get different healthcare as they age
By
Elissa Ball
23 September 2020 | 3 min read
Almost one-third of autistic children in the United States live in poverty
Children younger than age 5 and Black and Hispanic children on the spectrum experience the most financial hardships.
Almost one-third of autistic children in the United States live in poverty
By
Elissa Ball
19 August 2020 | 1 min read
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Sharing Africa’s brain data: Q&A with Amadi Ihunwo
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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.
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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.
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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