Jeremy Hsu is a science and technology journalist who writes for publications such as Scientific American, Discover, Wired, IEEE Spectrum and Undark. His recent focus has been on how artificial intelligence techniques such as deep learning could impact society.
Jeremy Hsu
From this contributor
How scientists secure the data driving autism research
Protecting the privacy of autistic people and their families faces new challenges in the era of big data.
How scientists secure the data driving autism research
By
Jeremy Hsu
30 September 2020 | 16 min read
Un ordinateur peut-il diagnostiquer l’autisme?
L’apprentissage automatique (machine learning) présente une possibilité pour aider les cliniciens à repérer l'autisme plus tôt, mais des obstacles techniques et éthiques demeurent.
Why are there so few autism specialists?
A lack of interest, training and pay may limit the supply of specialists best equipped to diagnose and treat children with autism.
Can a computer diagnose autism?
Machine-learning holds the promise to help clinicians spot autism sooner, but technical and ethical obstacles remain.
Explore more from The Transmitter
Leucovorin saga, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 15 June.
Leucovorin saga, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 15 June.
By
Jill Adams
16 June 2026 | 2 min read
Models at the speed of thought: How AI coding is reshaping theoretical neuroscience
Agentic coding makes it possible to specify a neuroscience model in hours instead of months. Six neuroscientists weigh in on what that tectonic change may bring to the field.
Models at the speed of thought: How AI coding is reshaping theoretical neuroscience
Agentic coding makes it possible to specify a neuroscience model in hours instead of months. Six neuroscientists weigh in on what that tectonic change may bring to the field.
By
Brian DePasquale
16 June 2026 | 17 min read
Writing science that humans and machines can read
Large language models are now routinely used to search, summarize and synthesize the literature at scales impossible for any individual researcher—yet scientific publishing has not adapted to that reality.
Writing science that humans and machines can read
Large language models are now routinely used to search, summarize and synthesize the literature at scales impossible for any individual researcher—yet scientific publishing has not adapted to that reality.
By
Rachel Parkinson
15 June 2026 | 7 min read