My interests are Computational Linguistics, Machine Learning and Neuroscience. My work combines all three of these areas to study the way the human brain processes language.
Models of language meaning (semantics) are typically built using large bodies of text (corpora) collected from the Internet. These corpora often contain billions of words, and thus cover the majority of the ways words are used. However, to build computer programs that truly understand language, and can understand more rare and nuanced word usage, we need algorithms that can generalize beyond common word usage. By collecting brain images of people reading, we can explore how the human brain handles the complexities of language, which could inspire the next generation of semantic models.