John Hewitt

Hello! I’m a PhD student in computer science, conducting research in natural language processing at Stanford University.

I design and analyze machine learning models of human languages. I tend to think we can figure out what deep neural networks learn about language, and use these insights to design models that learn from less data. As an undergraduate at Penn, I worked in the lab of Chris Callison-Burch.

I’m particularly interested in pursuing advances that permit the use of NLP across all languages, all domains, and all use cases – to increase access to NLP technologies.

Feel free to look me up on Google Scholar or Twitter, or take my CV.


  • [March 2019] I’m presenting a poster on syntax in unsupervised representations of language at the Stanford Human-Centered Artificial Intelligence Institute Symposium
  • [Feb 2019] My work with Chris Manning on methods for finding syntax trees embedded in contextual representations of language has been accepted to NAACL 2019!
  • [Oct 2018] I’ve started offering office hours for research-interested Stanford undergraduates!

Research Office Hours for Undergraduates (ROHU)

ROHU is cancelled Wednesday, April 10 due to the SAIL Workshop.

An open time for undergraduates looking for advice and discussions on natural language processing research. learn more

  • When Wednesdays, 6:00-7:00 PM
  • Where Gates Building, 2nd floor, A-wing big middle room
  • Who You, Stanford undergraduates wanting to chat about research; me, wanting to help
  • Publications
  • Blog
  • Projects
  • About


    Scott Aaronson’s old note on frameworks for reasoning about large numbers, for enjoyment

    Kevin Knight’s note on unix commands, to help you with your bash skills

    I highly suggest Arch Linux for its configurability and the educational experience it provides…


    Take my school email johnhew@stanford, and predict the TLD using your internal knowledge base.

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