Chair and Professor of Linguistics, Yale University
Professor Robert Frank studies the nature of human linguistic knowledge, how it is acquired and how it is processed. He is a cognitive scientist, seeking to connect insights garnered from a range of methodological approaches to construct a unified understanding of the human language faculty. He is interested in applying insights from computational modeling and the theory of computation to questions in the cognitive science of language. His work in the Tree Adjoining Grammar (TAG) formalism, for which he is particularly well-known, demonstrates that the restrictions embodied in TAG on the computational power of the operations that construct sentences yield elegant and explanatory analyses of a wide range of grammatical phenomena. Recently, Professor Frank has been exploring the viability of “big data” and machine learning approaches to language learning (including Bayesian modeling and neural networks), with results that point to the potential of inductive approaches to explain some aspects of language learning, but which also demonstrate the importance of innate constraint on linguistic structure. He has published a book, Phrase Structure Composition and Syntactic Dependencies (MIT Press), and numerous scientific articles, and has taught and lectured widely in North and South America and Europe.