John Hewitt

Hello! I’m a first-year PhD student in computer science, conducting research in natural language processing at Stanford University. I am grateful to be co-advised by Chris Manning and Percy Liang.

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.


  • [August 2019] My work with Percy Liang on designing and understanding neural probes with random control tasks has been accepted to EMNLP! Preprint soon.
  • [July 2019] I’m giving a talk at Amazon AI on finding and understanding emergent linguistic structure in neural NLP!
  • [June 2019] Gave a talk at NAACL’19 on structural probes! PDF of the slides now available.
  • [April 2019] I had a great time being interviewed by Waleed Ammar and Matt Gardner on structural probes! You can find the new NLP Highlights podcast episode on the topic here.
  • [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)

An open time for undergraduates looking for advice and discussions on natural language processing research. learn more. On hiatus for the summer, but feel free to reach out!

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    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

    The Fundamental Whiteboard Difficulty (Scott Aaronson):

    I figured that chalk has its problems—it breaks, the dust gets all over—but I could live with them, much more than I could live with the Fundamental Whiteboard Difficulty, of all the available markers always being dry whenever you want to explain anything.

    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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