About me

I am a research scientist at Google. My research focuses on machine learning and language understanding.

Prior to this, I was a Ph.D. student at Stanford University 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.

• 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: kguu 🐌 stanford.edu
• Github: @kelvinguu
• LinkedIn: kelvinguu
• Twitter: @kelvin_guu (that’s @kelvin_guu with an underscore; recently changed from @ke1vin)
• Google Scholar: Kelvin Guu