Dr. Jessica L. Montag
Jessica Montag studies how language abilities emerge with experience across the lifespan, including language comprehension, production, and reading. Dr. Montag uses varied methods and measures, including comprehension and production experiments in adults and children, compilation and analyses of text and speech corpora, and advanced quantitative methods.
Dr. Jon A. Willits
Jon Willits studies language and learning in infants, children, adults, and machines. His research uses computational, neurobiological, experimental, and naturalistic methods to better understand how people and machines learn, represent, and use languages and other forms of complex knowledge, especially word meanings and semantic knowledge.
Anastasia Stoops studies how people learn and use language over the lifespan in order to improve cognitive remediation interventions in the educational and medical settings. She uses psychophysical behavioral paradigms coupled with eye-tracking and electrophysiological recordings.
Philip Huebner studies computational models of language acquisition, and in particular RNN and Transformer-based language models.
Andrew Flores studies vocabulary and semantic development in infants and toddlers.
Lin Khern Chia
Lin Khern studies semantic memory with behavioral paradigms and computational models.
Emily Mech utilizes event-related potentials (ERPs), computational modeling, and behavioral methodology to examine how regularities in language and the world interact to affect the ways in which our linguistic and semantic knowledge is learned, structured, accessed, and communicated.
Shufan Mao is interested in representation of semantics, concept, and meanings. He is working on a distributional representation of concept and semantics using a network model which integrates distributional semantics, formal semantics and network science.
Jacki Erens is interested in various aspects of language production, at both the word and sentence level.
Jingfeng Zhang is interested in developing statistical and neurally-inspired models of learning, and examining how the structure of environmental input affects the efficiency of computational models. He is working on a project that aims to create a simulation of humans in a natural environment, using neural networks built with Unity3d to visualize the learning process