Emily writes frequently about autism and related issues, and her work has appeared in print or online at Discover, New York Times, Slate, Washington Post, San Francisco Chronicle, and others. Emily has a B.A. in English with minors in German and History and a Ph.D. in biological sciences, both from The University of Texas at Austin. She also completed postdoctoral work at the University of California, San Francisco and has taught graduate and undergraduate biology for many years.
Emily Willingham
Science writer
Spectrum
From this contributor
The legacy of Steve Silberman and his book, ‘NeuroTribes’
The writer’s empathic storytelling changed how society—and researchers—view autistic people.
The legacy of Steve Silberman and his book, ‘NeuroTribes’
By
Emily Willingham
26 September 2024 | 8 min read
Spotted around the web: Week of 29 October 2018
Here is a roundup of news and research for the week of 29 October.
Spotted around the web: Week of 29 October 2018
By
Emily Willingham
2 November 2018 | 5 min read
Book Review: A mother finds reward in risk
In “The Boy Who Loved Too Much,” a woman tries to cocoon her son, who has Williams syndrome, from life’s insults but later realizes her protective instincts carry dangers of their own.
Book Review: A mother finds reward in risk
By
Emily Willingham
30 October 2018 | 5 min read
Spotted around the web: Week of 22 October 2018
Here is a roundup of news and research for the week of 22 October.
Spotted around the web: Week of 22 October 2018
By
Emily Willingham
26 October 2018 | 4 min read
Spotted around the web: Week of 15 October 2018
Here is a roundup of news and research for the week of 15 October.
Spotted around the web: Week of 15 October 2018
By
Emily Willingham
19 October 2018 | 4 min read
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Neuroscience has become increasingly concerned with prediction, and machine learning with causal explanation, with each field adopting methods from the other. I asked eight experts to weigh in on what we stand to learn from this exchange.
Trading places: What happens when neuroscience turns into machine learning, and machine learning turns into neuroscience?
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