I use computational and experimental methods to study language and the mind, particularly (1) the cognitive processes that allow us to understand the things we hear and read so quickly, (2) the learning signals that we leverage as children to acquire language from the environment, and (3) the role played by real-time information processing constraints in shaping language learning and comprehension.
I often build deep learning models to investigate these questions, and I’m actively developing machine learning techniques to help scientists understand complex dynamical systems like the human mind and brain. My work intersects machine learning, cognitive science, neuroscience, artificial intelligence, natural language processing, statistics, and (psycho)linguistics.
I’ve also done some linguistic analysis of Guaraní (spoken in Paraguay) and Iyasa (spoken in Cameroon).
- Cur Dir Psych SciSimilarity of computations across domains does not imply shared implementation: The case of language comprehensionCurrent Directions in Psychological Science 2021
- ACLCDRNN: Discovering complex dynamics in human language processingIn Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
- CognitionContinuous-time deconvolutional regression for psycholinguistic modelingCognition 2021
- CoNLLBest Paper AwardAcquiring language from speech by learning to remember and predictIn Proceedings of the 24th Conference on Computational Natural Language Learning 2020
- NpsyfMRI reveals language-specific predictive coding during naturalistic sentence comprehensionNeuropsychologia 2020