Dan Parker

Dan Parker studies how people understand sentences in real time, focusing on how memory retrieval processes cause errors and illusions during language comprehension (for example, mistakenly agreeing a verb with the wrong noun, or misinterpreting negation or reflexive pronouns). His work combines behavioral experiments with computational and mathematical models, including comparisons to modern machine-learning approaches like transformer attention, to explain how the mind retrieves and combines linguistic information during sentence processing.

Publication output was concentrated heavily around 2017-2020 (peaking in 2019), followed by a sparse and irregular period from 2021-2026 with only a few outputs, suggesting a slowing pace over the last decade.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026