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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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People

Our researchers drive advancements in computer science through both fundamental and applied research.
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Foundational ML & Algorithms

Algorithms & Theory

Data Management

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Machine Intelligence

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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

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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

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Science, AI & Society

Climate & Sustainability

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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

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

We make products, tools, and datasets available to everyone with the goal of building a more collaborative ecosystem.
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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

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

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

Srikumar Ramalingam

Srikumar Ramalingam

Research Areas

Authored Publications

Google

Rethinking FID: Towards a Better Evaluation Metric for Image Generation

Sadeep Jayasumana

Srikumar Ramalingam

Andreas Veit

Daniel Glasner

Ayan Chakrabarti

Sanjiv Kumar

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2024)

MarkovGen: Structured Prediction for Efficient Text-to-Image Generation

Sadeep Jayasumana

Daniel Glasner

Srikumar Ramalingam

Andreas Veit

Ayan Chakrabarti

Sanjiv Kumar

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2024)

Learning ABCs: Approximate Bijective Correspondence for isolating factors of variation with weak supervision

Ameesh Makadia

Kieran Alexander Murphy

Srikumar Ramalingam

Varun Jampani

Computer vision and pattern recognition (CVPR) 2022 (to appear)

Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold

Kieran Alexander Murphy

Carlos Esteves

Varun Jampani

Srikumar Ramalingam

Ameesh Makadia

ICML (2021)

Balancing Robustness and Sensitivity using Feature Contrastive Learning

Seungyeon Kim

Daniel Glasner

Srikumar Ramalingam

Cho-Jui Hsieh

Kishore Papineni

Sanjiv Kumar

(2021)

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