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.
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Areas of interest: artificial intelligence, machine learning, deep learning, natural language processing, semantic parsing, reinforcement learning, statistics
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Applications of interest: voice user interfaces, natural language interfaces, AI-human hybrid systems, AI in healthcare, recommender systems
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Fellowships:
- NSF Graduate Research Fellowship (2012-2015)
- Stanford Math+X Fellowship (2012-2013)
- Greylock X (2017)
Timeline
Education
2012 - 2018 | Ph.D. in Statistics at Stanford University |
Advisor: Percy Liang. Ph.D. Committee: Percy Liang, Wing Hung Wong, Chris Manning, and Lester Mackey. | |
2007 - 2011 | B.S. in Mathematics at Duke University |
Work experience
2018 - Present | Research Scientist at Google AI |
Developing new methods for machine learning and natural language processing. | |
2018 - Present | Lecturer at Stanford University |
Teaching core topics in artificial intelligence (CS221) to 700+ Stanford students. | |
Summer 2015 | Ph.D. Software Engineering Intern at Google |
Worked with Senior Staff Software Engineer Jakob Uszkoreit on applied natural language processing projects. | |
Winter 2014/15 | Research Consultant at MetaMind |
Deep learning startup acquired by Salesforce in 2016. Worked with Founder & CEO/CTO Richard Socher. | |
2011 - 2012 | Researcher in Bayesian Statistics at Duke University |
Research with Professors David B. Dunson and Alex Hartemink. | |
Summer 2010 | Software Engineering and Product Management Intern at Redwood Systems |
Cleantech lighting automation startup founded by ex-Cisco executives and acquired in 2013 by CommScope. |
Publications
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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@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}, }
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Transforming Question Answering Datasets Into Natural Language Inference Datasets
Dorottya Demszky*, Kelvin Guu*, Percy Liang
arXiv preprint, 2018
(* equal contribution)@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} }
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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)@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}, }
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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)@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}, }
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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@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}, }
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Best paper honorable mention
Traversing Knowledge Graphs in Vector Space
Kelvin Guu, John Miller, Percy Liang
Empirical Methods in Natural Language Processing (EMNLP), 2015@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}, }
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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 -
Light timeout optimization
Xin Gu, Kelvin Gu1, Deepak Nulu
Redwood Systems
US Patent No. 8,538,596, 2013
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.
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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