About
Hi, I’m a senior staff research scientist & manager at Google DeepMind, where my team and I develop new methods for machine learning and language understanding.
Prior to this, I completed my Ph.D. 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 machine learning 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.
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Areas of interest: 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, machine learning in healthcare, recommender systems
News
Media coverage of my team’s recent work on Bard (double-check Bard’s responses with the “Google it” button):
- Google Keyword Blog: “Bard can now connect to your Google apps and services: Use Bard alongside Google apps and services, easily double-check its responses and access features in more places.”
- New York Times: “Google Connects A.I. Chatbot Bard to YouTube, Gmail and More Facts”
- CNN: “Google rolls out a major expansion of its Bard AI chatbot”
- Ars Technica: “Google’s AI assistant can now read your emails, plan trips, ‘double-check’ answers”
- Vox: “Google’s free AI isn’t just for search anymore”
Some semi-recent appearances:
- [Spring 2023] No Priors Podcast with investors Sarah Guo and Elad Gil
- [Spring 2022] Stanford CS224N NLP with Deep Learning (Spring 2022) Guest Lecture: Building Knowledge Representation
- [Winter 2020] Generally Intelligent Podcast with Kanjun Qiu and Josh Albrecht, founders of Imbue
Experience
Work
2018 - Present | Senior Staff Research Scientist, Manager at Google |
Developing new methods for machine learning and natural language processing | |
2018 - 2019 | 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 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. |
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. Fellowships: - NSF Graduate Research Fellowship (2012-2015) - Stanford Math+X Fellowship (2012-2013) - Greylock X Fellow (2017) |
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2007 - 2011 | B.S. in Mathematics at Duke University |
Minor in Biology |
Selected publications
Sorry, I’m not great at keeping this section updated. For a more comprehensive list of recent work, please check out my Google Scholar profile.
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Simfluence: Modeling the influence of individual training examples by simulating training runs
Kelvin Guu*, Albert Webson*, Ellie Pavlick, Lucas Dixon, Ian Tenney, Tolga Bolukbasi*
arXiv preprint, 2023
(* lead contributors) -
RARR: Researching and revising what language models say, using language models
Luyu Gao*, Zhuyun Dai*, Panupong Pasupat*, Anthony Chen*, Arun Tejasvi Chaganty*, Yicheng Fan*, Vincent Zhao, Ni Lao, Hongrae Lee, Da-Cheng Juan, Kelvin Guu*
Association for Computational Linguistics (ACL), 2023
(* lead contributors) -
Finetuned language models are zero-shot learners
Jason Wei*, Maarten Bosma*, Vincent Y Zhao*, Kelvin Guu*, Adams Wei Yu, Brian Lester, Nan Du, Andrew M Dai, Quoc V Le
International Conference on Learning Representations (ICLR), 2022
(* lead contributors) -
REALM: Retrieval-augmented language model pre-training
Kelvin Guu*, Kenton Lee*, Zora Tung, Panupong Pasupat, Ming-Wei Chang
International Conference on Machine Learning (ICML), 2020
(* equal contribution) -
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) -
Traversing Knowledge Graphs in Vector Space
Kelvin Guu, John Miller, Percy Liang
Empirical Methods in Natural Language Processing (EMNLP), 2015
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.
Collaborators
I have had the privilege of working with and learning from great mentors and collaborators, including but not limited to:
- Mentors
- Percy Liang, Associate Professor of Computer Science & Statistics at Stanford
- Jakob Uszkoreit, CEO and Co-Founder of Inceptive
- Richard Socher, CEO and Founder of you.com
- David B. Dunson, Professor of Statistics at Duke
- Debdeep Pati, Professor of Statistics at Texas A & M
- Alex Hartemink, Professor of Computer Science & Biology at Duke
- Ronald Parr, Professor of Computer Science at Duke
- Collaborators
- Tatsunori B. Hashimoto, Assistant Professor of Computer Science at Stanford
- Panupong (Ice) Pasupat, Senior Research Scientist at Google
- Dan Iter, Senior Research Scientist at Microsoft
- Evan Z. Liu, Researcher @ Imbue
- Dorottya (Dora) Demszky, Assistant Professor in Education Data Science at Stanford
- Justin Fu, Research Scientist at Waymo
Other interests
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
- Email:
kelvin 🐌 kelvinguu.com
- Twitter: @kelvin_guu
- Github: @kelvinguu
- Google Scholar: Kelvin Guu
- LinkedIn: kelvinguu