The overarching theme of our interdisciplinary research is the human ability to understand language on a word by word basis, quickly and robustly, across the languages of the world and across demographics and levels of academic achievement. To uncover the principles underlying this ability we use a broad range of research methods including eye-tracking studies of reading behavior, web-based experiments with tens of thousands of participants, Bayesian data analyses, and computational cognitive models. We conduct this research with partners in multiple disciplines and at instutions all over the world.
Specific topics that we work on:
- Assessment of reading ability using eye-tracking and machine learning
- Cognitive factors shaping the languages of the world
- Comparison of state-of-the-art eye-tracking systems
- Implicit gender biases in language
- Function and processing of resumptive pronouns across languages
- Role of working memory in sentence comprehension
- Statistical methods, especially those used for analyzing eye movements in reading
- Suspended compositionality in German bracketing paradoxes
See [here](https://www.nytimes.com/2020/01/24/us/politics/woman-president-she-her.html) for an New York Times article about our research on linguistic gender biases in the 2016 US presidential race.