Somer Bishop is a clinical psychologist and professor in residence of psychiatry at the University of California, San Francisco.
Somer Bishop
Assistant professor
University of California, San Francisco
From this contributor
Rethinking autism assessments in the time of COVID-19: Q&A with Bishop, Zwaigenbaum
Moving most clinical assessments online during the coronavirus pandemic has created a digital divide while closing some geographical ones, say Somer Bishop and Lonnie Zwaigenbaum.
Rethinking autism assessments in the time of COVID-19: Q&A with Bishop, Zwaigenbaum
Questions for Bishop, Havdahl: Tantrums trick autism tests
Children with low intelligence or behavioral issues — but not autism — may meet the criteria for autism on standard diagnostic tests.
Questions for Bishop, Havdahl: Tantrums trick autism tests
Seeking precise portraits of girls with autism
Researchers need to consider new ways of capturing how autism manifests in girls, who may find clever ways of camouflaging their symptoms.
Gauging intelligence in autism over time
Adapting traditional tests of intelligence for people with intellectual disability can deflate their scores over time. Somer Bishop calls for tests that more accurately assess intelligence in this group.
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.
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.
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.