About me

I’m a research scientist at Google AI, where I develop new methods for machine learning and language understanding.

I was previously a Ph.D. student at Stanford advised by Percy Liang in the Stanford Natural Language Processing Group. I completed my undergraduate degree in mathematics at Duke University, where I was advised by David Dunson and Alex Hartemink.

Long-term, I hope to make artificial intelligence so cheap and easy that everyone can use it for their benefit, not just organizations with big datasets or deep pockets. I’m also excited about improving collective intelligence — making society smarter than the sum of its parts.

• Areas of interest: artificial intelligence, machine learning, deep learning, natural language processing, semantic parsing, reinforcement learning, statistics

• Applications of interest: voice user interfaces, natural language interfaces, AI-human hybrid systems, AI in healthcare, recommender systems

• Fellowships:

  • NSF Graduate Research Fellowship (2012-2015)
  • Stanford Math+X Fellowship (2012-2013)
  • Greylock X (2017)

Timeline

Education

Work experience

Publications

• A Retrieve-and-Edit Framework for Predicting Structured Outputs
  Tatsunori B. Hashimoto, Kelvin Guu, Yonatan Oren, Percy Liang
  Advances in Neural Information Processing Systems (NIPS), 2018

  

• Mapping Natural Language Commands to Web Elements
  Panupong Pasupat, Tian-Shun Jiang, Evan Liu, Kelvin Guu, Percy Liang
  Empirical Methods in Natural Language Processing (EMNLP), 2018

  pdf arxiv bibtex

  @inproceedings{pasupat2018mapping,
    title={Mapping natural language commands to web elements},
    author={Pasupat, Panupong and Jiang, Tian-Shun and Liu, Evan and Guu, Kelvin and Liang, Percy},
    booktitle = {Empirical Methods in Natural Language Processing (EMNLP)},
    year = {2018},
  }
  
  

  

• Transforming Question Answering Datasets Into Natural Language Inference Datasets
  Dorottya Demszky*, Kelvin Guu*, Percy Liang
  arXiv preprint, 2018
  (* equal contribution)

  pdf arxiv github codalab bibtex

  @article{demszky2018transforming,
    title={Transforming Question Answering Datasets Into Natural Language Inference Datasets},
    author={Demszky, Dorottya and Guu, Kelvin and Liang, Percy},
    journal={arXiv preprint arXiv:1809.02922},
    year={2018}
  }
  

  

• Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration
  Kelvin Guu*, Evan Z. Liu*, Panupong Pasupat*, Tianlin Shi, Percy Liang
  International Conference on Learning Representations (ICLR), 2018
  (* equal contribution)

  pdf arxiv github bibtex

  @inproceedings{guu2018web,
    title = {Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration},
    author = {Guu, Kelvin and Liu, Evan Z. and Pasupat, Panupong and Shi, Tianlin and Liang, Percy},
    booktitle = {International Conference on Learning Representations (ICLR)},
    year = {2018},
  }
  

  

• Generating Sentences by Editing Prototypes
  Kelvin Guu*, Tatsunori B. Hashimoto*, Yonatan Oren, Percy Liang
  Transactions of the Association for Computational Linguistics (TACL), 2018
  (* equal contribution)

  pdf arxiv slides github codalab bibtex

  @inproceedings{guu2018generating,
    title = {Generating Sentences by Editing Prototypes},
    author = {Guu, Kelvin and Hashimoto, Tatsunori B. and Oren, Yonatan and Liang, Percy},
    booktitle = {Transactions of the Association for Computational Linguistics (TACL)},
    year = {2018},
  }
  

  

• From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood
  Kelvin Guu, Panupong Pasupat, Evan Liu, Percy Liang
  Association for Computational Linguistics (ACL), 2017

  pdf arxiv slides github codalab bibtex

  @inproceedings{guu2017bridging,
    title = {From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood},
    author = {Guu, Kelvin and Pasupat, Panupong and Liu, Evan Zheran and Liang, Percy},
    booktitle = {Association for Computational Linguistics (ACL)},
    year = {2017},
  }
  

  

• Best paper honorable mention
  Traversing Knowledge Graphs in Vector Space
  Kelvin Guu, John Miller, Percy Liang
  Empirical Methods in Natural Language Processing (EMNLP), 2015

  pdf arxiv slides codalab bibtex

  @inproceedings{guu2015traversing,
    title = {Traversing Knowledge Graphs in Vector Space},
    author = {Guu, Kelvin and Miller, John and Liang, Percy},
    booktitle = {Empirical Methods in Natural Language Processing (EMNLP)},
    year = {2015},
  }
  

  

• Bayesian Multiscale Modeling of Closed Curves in Point Clouds
  Kelvin Gu¹, Debdeep Pati, David B. Dunson
  Journal of the American Statistical Association Vol. 109 (508), 2014

  pdf ncbi

  

• Light timeout optimization
  Xin Gu, Kelvin Gu¹, Deepak Nulu
  Redwood Systems
  US Patent No. 8,538,596, 2013

  pdf google patents

  

Other projects

Presentations and tutorials

• Why naive cross-validation can fail for feature selection.
• Presentation on selection and multiple hypothesis testing, based on several great lectures by Emmanuel Candes.
• Presentation on random matrices, prepared for Percy Liang’s reading group.

Libraries

Unfortunately, much of my recent code is closed-source at the moment, but I’m working on getting it cleaned up and ready for others to use! The following projects are fairly old/out-of-date, but I’m keeping them around in the odd chance they might be of use to someone somewhere.

• Simple Speech Recognition - 2013
  A complete speech recognition system you can deploy with just a few lines of Python, built on CMU Sphinx-4.

• Gitmemoizer - 2013
  Automagically memoize any function and save results to disk (for Java).

• Giterable - 2013
  A Java package for iterating through files in your Git repo and loading them.

Collaborators

I have had the privilege of working with and learning from great mentors and collaborators, including:

• Percy Liang, Assistant Professor of Computer Science at Stanford
• Panupong (Ice) Pasupat, Ph.D. Student in Computer Science at Stanford
• Tatsunori B. Hashimoto, Postdoctoral Fellow in Computer Science and Statistics at Stanford
• Jakob Uszkoreit, Senior Staff Software Engineer at Google
• Richard Socher, Chief Scientist at Salesforce
• David B. Dunson, Professor of Statistics at Duke
• Debdeep Pati, Assistant Professor of Statistics at Florida State
• Alex Hartemink, Professor of Computer Science at Duke
• Ronald Parr, Professor of Computer Science at Duke

I’ve enjoyed mentoring younger students, including:

• John Miller, undergraduate in Computer Science at Stanford, currently EECS PhD student at UC Berkeley
• Justin Fu, MS in Computer Science at Stanford, currently EECS PhD student at UC Berkeley
• Dora Demszky, undergraduate in linguistics at Princeton, currently Linguistics PhD student at Stanford
• Evan Liu, undergraduate and master’s student in Computer Science at Stanford

Finally, I think the following entities are pretty swell:

• Doug Engelbart. We still need to finish this guy’s mission.
• Wikipedia and Freebase.
• Jon Kabat-Zinn. For bringing scientific attention to the study of mindfulness.
• The Bill & Melinda Gates Foundation. I think they make a huge impact by bringing an investor’s mindset to important and good causes.

Contact

• Office: Gates Computer Science Building, Room 2^8
• Email: kelvin 🐌 kelvinguu.com (apologies, my old stanford.edu email has been bouncing lately, so this is the best way to reach me at the moment)
• Github: @kelvinguu
• LinkedIn: kelvinguu
• Twitter: @kelvin_guu (that’s @kelvin_guu with an underscore; recently changed from @ke1vin)
• Google Scholar: Kelvin Guu