Katherine E. Twomey
University of Manchester, University of Sussex, Lancaster University, University of Trento
Papers
7
Total Citations
44
H-Index
4
About
Katherine E. Twomey is a developmental cognitive scientist whose research sits at the intersection of infant learning, language acquisition, and computational modeling. Her work fundamentally challenges representational theories of early cognitive development, arguing instead that skills like gaze following and word learning emerge through embodied, experience-driven processes. In a landmark series of papers, Twomey demonstrated that infants learn to follow gaze in distinct stages, a prediction first generated by her robotic models—a powerful example of how computational approaches can inform developmental theory. Her research on categorization and word learning (2013) shows how children’s categories and labels are interdependent, while her 2019 study revealed that extraneous perceptual information, such as object color, can actually hinder word learning by distracting from relevant features. Twomey’s work on competitive dynamics in word learning (2016) further shows how mutual exclusivity processes operate in real-time learning. With over 40 citations across her most-cited papers, Twomey is a leading voice in the use of developmental robotics and neural network modeling to test and refine theories of early cognition, offering a rigorous, mechanistic account of how infants build their first words and social understanding.
Research Focus
Key Achievements
Top Papers
- 1
- 2An Embodied Model of Young Children’s Categorization and Word Learning10 citations · 2013
- 3
- 4Competition Affects Word Learning in a Developmental Robotic System6 citations · 2016
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- 6
- 7An investigation of fast and slow mapping2 citations · 2012