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Defining the technology of today and tomorrow.

Philosophy

We strive to create an environment conducive to many different types of research across many different time scales and levels of risk.
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Philosophy

People

Our researchers drive advancements in computer science through both fundamental and applied research.
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People
Research areas

Explore all research areas

Explore all research areas

Foundational ML & Algorithms

Algorithms & Theory

Data Management

Data Mining & Modeling

Information Retrieval & the Web

Machine Intelligence

Machine Perception

Machine Translation

Natural Language Processing

Speech Processing

Algorithms & Theory

Data Management

Data Mining & Modeling

Information Retrieval & the Web

Machine Intelligence

Machine Perception

Machine Translation

Natural Language Processing

Speech Processing

Computing Systems & Quantum AI

Distributed Systems & Parallel Computing

Hardware & Architecture

Mobile Systems

Networking

Quantum Computing

Robotics

Security, Privacy, & Abuse Prevention

Software Engineering

Software Systems

Distributed Systems & Parallel Computing

Hardware & Architecture

Mobile Systems

Networking

Quantum Computing

Robotics

Security, Privacy, & Abuse Prevention

Software Engineering

Software Systems

Science, AI & Society

Climate & Sustainability

Economics & Electronic Commerce

Education Innovation

General Science

Health & Bioscience

Human-Computer Interaction and Visualization

Climate & Sustainability

Economics & Electronic Commerce

Education Innovation

General Science

Health & Bioscience

Human-Computer Interaction and Visualization
Projects

We regularly open-source projects with the broader research community and apply our developments to Google products.
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Projects

Publications

Publishing our work allows us to share ideas and work collaboratively to advance the field of computer science.
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Publications

Resources

We make products, tools, and datasets available to everyone with the goal of building a more collaborative ecosystem.
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Resources
Shaping the future, together.
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Student programs

Supporting the next generation of researchers through a wide range of programming.
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Student programs

Faculty programs

Participating in the academic research community through meaningful engagement with university faculty.
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Faculty programs

Conferences & events

Connecting with the broader research community through events is essential for creating progress in every aspect of our work.
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Conferences & events

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Careers
Blog

Shanshan Wu

Currently working on federated learning and personalization. Previously received my PhD from UT Austin: https://wushanshan.github.io/

Authored Publications

Google

Federated Reconstruction: Partially Local Federated Learning

Karan Singhal

Hakim Sidahmed

Zachary Garrett

Shanshan Wu

Keith Rush

Sushant Prakash

Arxiv (2021)

A Field Guide to Federated Optimization

Jianyu Wang

Zachary Burr Charles

Zheng Xu

Gauri Joshi

Brendan McMahan

Blaise Hilary Aguera-Arcas

Maruan Al-Shedivat

Galen Andrew

A. Salman Avestimehr

Katharine Daly

Deepesh Data

Suhas Diggavi

Hubert Eichner

Advait Gadhikar

Zachary Garrett

Antonious M. Girgis

Filip Hanzely

Andrew Hard

Chaoyang He

Samuel Horvath

Zhouyuan Huo

Alex Ingerman

Martin Jaggi

Tara Javidi

Peter Kairouz

Satyen Chandrakant Kale

Sai Praneeth Karimireddy

Jakub Konečný

Sanmi Koyejo

Tian Li

Luyang Liu

Mehryar Mohri

Hang Qi

Sashank Reddi

Peter Richtarik

Karan Singhal

Virginia Smith

Mahdi Soltanolkotabi

Weikang Song

Ananda Theertha Suresh

Sebastian Stich

Ameet Talwalkar

Hongyi Wang

Blake Woodworth

Shanshan Wu

Felix Yu

Honglin Yuan

Manzil Zaheer

Mi Zhang

Tong Zhang

Chunxiang (Jake) Zheng

Chen Zhu

Wennan Zhu

arxiv (2021)

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