Uta Frith


Uta Frith studied experimental psychology at the Universität des Saarlandes, Saarbrücken and trained in clinical psychology at the University of London’s Institute of Psychiatry She completed her Ph.D. thesis on autism in 1968 and from then on has worked as a research scientist funded mainly by the Medical Research Council UK. She has been Visiting Professor at the University of Aarhus, Denmark from 2007-2015. She is now Emeritus Professor of Cognitive Development at the UCL Institute of Cognitive Neuroscience.
Autism and dyslexia have been her main focus of research. In both fields she has pioneered an experimental neuropsychological approach. She has contributed some of the major theories explaining these disorders and has identified specific deficits in underlying cognitive mechanisms and their basis in the brain. She has published some 250 papers and books, and in 2014 she was listed by the APA as among the 200 most eminent psychologists of the modern era.
In the last few years she has increased her work in science communication, and in championing women in science.

From this contributor

Explore more from The Transmitter

Photograph of the BRIDGE team and students visiting a laboratory.

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.

By Lauren Schenkman
20 May 2025 | 6 min read
Research image of neurite overgrowth in cells grown from people with autism-linked PPP2R5D variants.

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.

By Jill Adams
20 May 2025 | 2 min read
Digitally distorted building blocks.

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.

By Alona Fyshe
19 May 2025 | 7 min read