Me in Montreal in December 2015.

Hi, I’m Jon Gauthier. I’m a Ph.D. student in the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology. I build computational models of how people learn, understand, and produce language. I collaborate with members of the Computational Psycholinguistics Laboratory and the Computational Cognitive Science Group, combining methods from artificial intelligence, linguistics, neuroscience, and philosophy. I also co-run the Brain and Cognitive Sciences Philosophy Circle.

Before joining MIT, I did research in natural language processing and machine learning at Stanford University in the Natural Language Processing Group, where I was advised by Christopher Manning. I also spent time as a researcher at OpenAI and Google Brain, where I mainly collaborated with Ilya Sutskever and Oriol Vinyals.

I had the good fortune to begin research at a young age, thanks to the generosity and support of my advisors and academic community. I’m interested in helping ambitious undergraduate students likewise break into the world of academia. Please get in touch!

Recent personal news


(Find me on Google Scholar for an up-to-date list.)

Reasoning about exceptions in a multidimensional space: A probabilistic account of multidimensional adjectives.
A rational model of syntactic bootstrapping.
Query-guided visual search.
Does the brain represent words? An evaluation of brain decoding studies of language understanding.
Word learning and the acquisition of syntactic–semantic overhypotheses.
Are distributional representations ready for the real world? Evaluating word vectors for grounded perceptual meaning.
A paradigm for situated and goal-driven language learning.
A fast unified model for parsing and sentence understanding.
Exploiting long-distance context in transition-based dependency parsing with recurrent neural networks.

Around the web

Currently reading

Currently reading

The Information: A History, a Theory, a Flood
tagged: mind-tickling and currently-reading
The Haskell Road to Logic, Maths and Programming
tagged: programming, haskell, functional-programming, math, mind-tickling, ...
Learning J
tagged: currently-reading and programming
On LISP: Advanced Techniques for Common LISP
tagged: currently-reading, lisp, and programming