Benjamin Yip is associate professor of public health and statistics at the Chinese University of Hong Kong. He is an epidemiologist who has led the development and application of statistical models to disentangle the genetic and environmental underpinnings of autism and other neuropsychiatric conditions.
Benjamin Yip
Associate professor of public health and statistics
Chinese University of Hong Kong
From this contributor
By
Sneha Chaturvedi, John Constantino, Natasha Marrus, Sven Sandin, Benjamin Yip
19 September 2024
6 min read
Autism is more heritable in boys than in girls
If boys have greater inherited liability for autism, the female protective effect may not fully explain the sex difference in prevalence.
Autism is more heritable in boys than in girls
By
Sneha Chaturvedi, John Constantino, Natasha Marrus, Sven Sandin, Benjamin Yip
19 September 2024 | 6 min read
Explore more from The Transmitter
Autism-linked genes alter sleep behavior, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 13 April.
Autism-linked genes alter sleep behavior, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 13 April.
By
Jill Adams
14 April 2026 | 2 min read
This paper changed my life: Erin Calipari ponders the nuances of rewarding and aversive stimuli
A 1960s study by Kelleher and Morse found that lever pressing in squirrel monkeys depended not on whether they received a reward or shock, but on the rules of the task. This taught Calipari to think deeply about factors that influence how behavior is generated and maintained.
This paper changed my life: Erin Calipari ponders the nuances of rewarding and aversive stimuli
A 1960s study by Kelleher and Morse found that lever pressing in squirrel monkeys depended not on whether they received a reward or shock, but on the rules of the task. This taught Calipari to think deeply about factors that influence how behavior is generated and maintained.
By
Erin Calipari
14 April 2026 | 5 min read
Why neural foundation models work, and what they might—and might not—teach us about the brain
These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity. But will we be able to understand them?
Why neural foundation models work, and what they might—and might not—teach us about the brain
These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity. But will we be able to understand them?
By
Juan Gallego
13 April 2026 | 8 min read