Claire Cui

Claire Cui

Claire is currently a Google Fellow in the Google Brain team, leading a team of researchers to push the forefront of machine learning research and apply it to solve high-impact problems for improving people's life.

During her tenure at Google, Claire co-initiated and launched many successful and sustainable projects. She was a founding engineer for Google’s AdSense for Content product, which was one of the first products in Google that used machine learning technologies. She later helped co-found Google Health Research and Medical Brain to work on machine learning for improving people's health.

Claire’s current research interests are around Deep Generalist Learning, including
- Large Scale General Language Model (e.g., GLaM)
- Self-Supervised Multimodal Learning
- Universal Representation Learning
- Model Uncertainty and Interpretability

Claire has a PhD in Computer Science from Stanford University and a bachelor of science degree in CS from Tsinghua University. She has two daughters, 16 and 12 yrs old. They share the love of playing volleyball as a hobby.

Authored Publications
Sort By
  • Title
  • Title, descending
  • Year
  • Year, descending
    Google
LaMDA: Language Models for Dialog Applications
Aaron Daniel Cohen
Alena Butryna
Alicia Jin
Apoorv Kulshreshtha
Ben Zevenbergen
Chung-ching Chang
Cosmo Du
Daniel De Freitas Adiwardana
Dehao Chen
Dmitry (Dima) Lepikhin
Erin Hoffman-John
Igor Krivokon
James Qin
Jamie Hall
Joe Fenton
Johnny Soraker
Kathy Meier-Hellstern
Maarten Paul Bosma
Marc Joseph Pickett
Marcelo Amorim Menegali
Marian Croak
Maxim Krikun
Noam Shazeer
Rachel Bernstein
Ravi Rajakumar
Ray Kurzweil
Romal Thoppilan
Steven Zheng
Taylor Bos
Toju Duke
Tulsee Doshi
Vincent Y. Zhao
Will Rusch
Yuanzhong Xu
Zhifeng Chen
arXiv (2022)
Sparsely Activated Language Models are Efficient In-Context Learners
Barret Richard Zoph
Dmitry (Dima) Lepikhin
Emma Wang
Kathy Meier-Hellstern
Kun Zhang
Liam B. Fedus
Maarten Paul Bosma
Marie Pellat
Maxim Krikun
Nan Du
Simon Tong
Tao Wang
Toju Duke
Yonghui Wu
Yuanzhong Xu
Zhifeng Chen
Zongwei Zhou
(2022)
Scalable and accurate deep learning for electronic health records
Alvin Rishi Rajkomar
Eyal Oren
Nissan Hajaj
Mila Hardt
Peter J. Liu
Xiaobing Liu
Jake Marcus
Patrik Per Sundberg
Kun Zhang
Yi Zhang
Gerardo Flores
Gavin Duggan
Jamie Irvine
Kurt Litsch
Alex Mossin
Justin Jesada Tansuwan
De Wang
Dana Ludwig
Samuel Volchenboum
Kat Chou
Michael Pearson
Srinivasan Madabushi
Nigam Shah
Atul Butte
npj Digital Medicine (2018)