I am an Associate Professor of Linguistics and Data Science at New York University, and a Research Scientist at Google. At NYU, I direct the Computation and Psycholinguistics Lab; we use behavioral experiments and computational methods to study how people learn and understand language. We also develop methods for evaluating, understanding and improving computational systems for language processing.

I am accepting PhD students for Fall 2025 through either Linguistics or Data Science; I look forward to reading your applications! Please read the FAQ before contacting me about PhD admissions.

Representative publications

Marten van Schijndel & Tal Linzen (2021). Single-stage prediction models do not explain the magnitude of syntactic disambiguation difficulty. Cognitive Science. [link] [pdf]

Tal Linzen (2020). How can we accelerate progress towards human-like linguistic generalization? ACL. [pdf]

R. Thomas McCoy, Robert Frank & Tal Linzen (2020). Does syntax need to grow on trees? Sources of hierarchical inductive bias in sequence-to-sequence networks. TACL. [arXiv]

Tal Linzen, Emmanuel Dupoux & Yoav Goldberg (2016). Assessing the ability of LSTMs to learn syntax-sensitive dependencies. TACL. [pdf]

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