2026 Noam Shazeer: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	39	9454	9181	3999	3832	81	48827

Overview

Noam Shazeer is affiliated with Google in the United States and has contributed extensively to the field of computer science, with a focus on artificial intelligence. Their research spans multiple key subfields such as computer vision and pattern recognition, information systems, hardware and architecture, and computer networks and communications.

The main topics covered in their work include:

Topic Modeling
Natural Language Processing Techniques
Multimodal Machine Learning Applications
Advanced Neural Network Applications
Domain Adaptation and Few-Shot Learning
Software Engineering Research
Parallel Computing and Optimization Techniques

Shazeer's recent scholarly output features publications in established venues such as arXiv (Cornell University), Leibniz-Zentrum für Informatik (Schloss Dagstuhl), and Zenodo (CERN European Organization for Nuclear Research). Notable papers include:

"MizAR 60 for Mizar 50," 2023, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
"PaLM: Scaling Language Modeling with Pathways," 2022, arXiv (Cornell University)
"LaMDA: Language Models for Dialog Applications," 2022, arXiv (Cornell University)
"Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity," 2021, arXiv (Cornell University)
"SAAP: A Normative and Segregated AGI Architecture Proposal," 2025, Zenodo (CERN European Organization for Nuclear Research)

Their network of frequent coauthors reflects collaboration with several researchers, including Sharan Narang, Hyung Won Chung, Noah Fiedel, William Fedus, and Barret Zoph. This suggests active engagement in joint research efforts across various projects and topics related to AI and machine learning.

Publication frequency shows a strong presence particularly in the arXiv repository, with 14 publications, indicating a preference for open-access preprint platforms. Other venues include the Leibniz-Zentrum für Informatik and proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, illustrating a focus on conferences and established repositories relevant to computational linguistics and AI research.

Overall, Shazeer's body of work contributes to advancing knowledge in artificial intelligence through a blend of theoretical models and applied techniques in natural language processing, multimodal learning, and scalable neural network architectures.

Best Publications

Attention is All you Need

Ashish Vaswani;Noam Shazeer;Niki Parmar;Jakob Uszkoreit

31113
Citations
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Colin Raffel;Noam Shazeer;Adam Roberts;Katherine Lee

5710
Citations
Scheduled sampling for sequence prediction with recurrent Neural networks

Samy Bengio;Oriol Vinyals;Navdeep Jaitly;Noam Shazeer

1722
Citations
Exploring the limits of language modeling

Rafal Jozefowicz;Oriol Vinyals;Mike Schuster;Noam Shazeer

1363
Citations
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Noam Shazeer;Azalia Mirhoseini;Krzysztof Maziarz;Andy Davis

901
Citations
Generating Wikipedia by Summarizing Long Sequences

Peter J. Liu;Mohammad Ahmad Saleh;Etienne Pot;Ben Goodrich

702
Citations
End-to-end text-dependent speaker verification

Georg Heigold;Ignacio Moreno;Samy Bengio;Noam Shazeer

696
Citations
How Much Knowledge Can You Pack Into the Parameters of a Language Model

Adam Roberts;Colin Raffel;Noam Shazeer

615
Citations
Tensor2Tensor for Neural Machine Translation

Ashish Vaswani;Samy Bengio;Eugene Brevdo;Francois Chollet

511
Citations
Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity.

William Fedus;Barret Zoph;Noam Shazeer

492
Citations
GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding

Dmitry Lepikhin;HyoukJoong Lee;Yuanzhong Xu;Dehao Chen

411
Citations
The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation

Mia Xu Chen;Orhan Firat;Ankur Bapna;Melvin Johnson

401
Citations
Music Transformer: Generating Music with Long-Term Structure

Cheng-Zhi Anna Huang;Ashish Vaswani;Jakob Uszkoreit;Noam Shazeer

367
Citations
One Model To Learn Them All

Lukasz Kaiser;Aidan N. Gomez;Noam Shazeer;Ashish Vaswani

339
Citations
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost

Noam Shazeer;Mitchell Stern

290
Citations
Model generation for ranking documents based on large data sets

Jeremy Bem;Georges R. Harik;Joshua L. Levenberg;Noam Shazeer

233
Citations
Image Transformer

Niki Parmar;Ashish Vaswani;Jakob Uszkoreit;Łukasz Kaiser

220
Citations
Mesh-TensorFlow: Deep Learning for Supercomputers

Noam Shazeer;Youlong Cheng;Niki J. Parmar;Dustin Tran

219
Citations
Fast Decoding in Sequence Models using Discrete Latent Variables

Łukasz Kaiser;Aurko Roy;Ashish Vaswani;Niki Parmar

204
Citations
Method and apparatus for characterizing documents based on clusters of related words

Georges Harik;Noam M. Shazeer

190
Citations
Music Transformer

Cheng-Zhi Anna Huang;Ashish Vaswani;Jakob Uszkoreit;Noam Shazeer

33
Citations
GLU Variants Improve Transformer.

Noam Shazeer

23
Citations

Frequent Co-Authors

Jakob Uszkoreit Inceptive

Ashish Vaswani Google (United States)

Samy Bengio Apple (United States)

Ciprian Chelba Google (United States)

Colin Raffel University of Toronto

Jeffrey Dean Google (United States)

Navdeep Jaitly Google (United States)

Oriol Vinyals DeepMind (United Kingdom)

Zhifeng Chen Google (United States)

Michael L. Littman Brown University

External Links

Personal website of Noam Shazeer Google Scholar page

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