2026 Yann N. Dauphin: 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	37	10425	10133	4352	4173	61	22432

Yann N. Dauphin publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Yann N. Dauphin sits on this spectrum.

32 publications 991+

This scientist: 61 publications — 1st percentile

1% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Yann N. Dauphin D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Yann N. Dauphin sits on this spectrum.

30 D-Index 131+

This scientist: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Yann N. Dauphin is a researcher primarily affiliated with Google in the United States. Their body of work is situated within the field of computer science, with a focus on artificial intelligence, computer vision and pattern recognition, health informatics, signal processing, and safety research.

Their research interests cover a range of topics, including:

Domain Adaptation and Few-Shot Learning
Advanced Neural Network Applications
Machine Learning and Data Classification
Generative Adversarial Networks and Image Synthesis
Machine Learning and Extreme Learning Machines (ELM)
Anomaly Detection Techniques and Applications
Adversarial Robustness in Machine Learning

Dauphin has contributed substantially to the academic literature, with publications primarily in prominent venues such as arXiv (Cornell University), the Proceedings of the AAAI Conference on Artificial Intelligence, PLoS ONE, and the Leibniz-Zentrum für Informatik (Schloss Dagstuhl).

Some of the recent papers authored or co-authored by Dauphin include:

Static Analysis of Shape in TensorFlow Programs, 2020, arXiv (Cornell University)
Mixup: Beyond empirical risk minimization, 2024, arXiv (Cornell University)
Continental-Scale Building Detection from High Resolution Satellite Imagery, 2021, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions, 2021, arXiv (Cornell University)
Gradient Flow in Sparse Neural Networks and How Lottery Tickets Win, 2022, Proceedings of the AAAI Conference on Artificial Intelligence

Their collaborations include frequent co-authorship with individuals such as:

Alina Beygelzimer
Percy Liang
Utku Evci
Atish Agarwala
Ekin D. Cubuk

Throughout their career, Dauphin has maintained a focus on advancing machine learning techniques, particularly in areas that intersect with neural networks and domain adaptation challenges. Their work has been disseminated through a variety of channels favored in the AI research community, reflecting engagement with both theoretical and applied aspects of artificial intelligence.

Best Publications

mixup: Beyond Empirical Risk Minimization

Hongyi Zhang;Moustapha Cisse;Yann N. Dauphin;David Lopez-Paz

5386
Citations
Convolutional Sequence to Sequence Learning

Jonas Gehring;Michael Auli;David Grangier;Denis Yarats

2811
Citations
Theano: A Python framework for fast computation of mathematical expressions

Rami Al-Rfou;Guillaume Alain;Amjad Almahairi

2208
Citations
Language modeling with gated convolutional networks

Yann N. Dauphin;Angela Fan;Michael Auli;David Grangier

1797
Citations
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

Yann N Dauphin;Razvan Pascanu;Caglar Gulcehre;Kyunghyun Cho

1397
Citations
Hierarchical Neural Story Generation

Angela Fan;Mike Lewis;Yann N. Dauphin

1343
Citations
Using recurrent neural networks for slot filling in spoken language understanding

Grégoire Mesnil;Yann Dauphin;Kaisheng Yao;Yoshua Bengio

672
Citations
Parseval networks: improving robustness to adversarial examples

Moustapha Cisse;Piotr Bojanowski;Edouard Grave;Yann Dauphin

564
Citations
Pay Less Attention with Lightweight and Dynamic Convolutions

Felix Wu;Angela Fan;Alexei Baevski;Yann N. Dauphin

539
Citations
EmoNets: Multimodal deep learning approaches for emotion recognition in video

Samira Ebrahimi Kahou;Xavier Bouthillier;Pascal Lamblin;Çaglar Gülçehre

506
Citations
A Convolutional Encoder Model for Neural Machine Translation

Jonas Gehring;Michael Auli;David Grangier;Yann N. Dauphin

480
Citations
Combining modality specific deep neural networks for emotion recognition in video

Samira Ebrahimi Kahou;Christopher Pal;Xavier Bouthillier;Pierre Froumenty

441
Citations
Unsupervised and Transfer Learning Challenge: a Deep Learning Approach

Grégoire Mesnil;Yann N. Dauphin;Xavier Glorot;Salah Rifai

416
Citations
Deal or No Deal? End-to-End Learning of Negotiation Dialogues

Mike Lewis;Denis Yarats;Yann N. Dauphin;Devi Parikh

364
Citations
Better Mixing via Deep Representations

Yoshua Bengio;Gregoire Mesnil;Gregoire Mesnil;Yann Dauphin;Salah Rifai

340
Citations
Higher order contractive auto-encoder

Salah Rifai;Grégoire Mesnil;Pascal Vincent;Xavier Muller

331
Citations
The Manifold Tangent Classifier

Salah Rifai;Yann N Dauphin;Pascal Vincent;Yoshua Bengio

319
Citations
Equilibrated adaptive learning rates for non-convex optimization

Yann N. Dauphin;Harm de Vries;Yoshua Bengio

274
Citations
Strategies for Structuring Story Generation

Angela Fan;Mike Lewis;Yann N. Dauphin

228
Citations
Empirical Analysis of the Hessian of Over-Parametrized Neural Networks

Levent Sagun;Utku Evci;V. Ugur Güney;Yann N. Dauphin

226
Citations
RMSProp and equilibrated adaptive learning rates for non-convex optimization.

Yann N. Dauphin;Harm de Vries;Junyoung Chung;Yoshua Bengio

216
Citations
Deal or No Deal? End-to-End Learning for Negotiation Dialogues

Mike Lewis;Denis Yarats;Yann N. Dauphin;Devi Parikh

33
Citations

Frequent Co-Authors

Yoshua Bengio University of Montreal

Michael Auli Facebook (United States)

David Grangier Google (United States)

Pascal Vincent Facebook (United States)

Aaron Courville University of Montreal

Gokhan Tur Amazon (United States)

Larry P. Heck Georgia Institute of Technology

Dilek Hakkani-Tur University of Illinois at Urbana-Champaign

Michael Lewis University of Pittsburgh

Caglar Gulcehre DeepMind (United Kingdom)

External Links

Personal website of Yann N. Dauphin Google Scholar page

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