INSPIRE: Gradient Symbolic Computation

The grant “INSPIRE: Gradient Symbolic Computation” combines computational modeling, formal linguistics, and behavioral psycholinguistics to develop a novel framework – Gradient Symbolic Computation – for integrating continuous and discrete aspects of cognition. Throughout the 4 years of the project, Matthew Goldrick will collaborate with researchers at Johns Hopkins on all aspects of this project, including computational and mathematical analysis and the writing of journal articles and conference presentations to disseminate these findings. In years 2-3 a postdoctoral fellow will also be involved in computational and mathematical analysis, assisting in the development of new computational tools. Goldrick will also supervise the design and execution of behavioral experiments of language processing that will be conducted in year 1 at Northwestern University. Goldrick will work with a graduate student to execute these experiments and disseminate their results through conference presentations and journal publications.