World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
30
Citations
18505
World Ranking
13801
National Ranking
5475

Alexis Conneau 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 Alexis Conneau sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 41 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.

Alexis Conneau 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 Alexis Conneau sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 30 D-Index — 3rd percentile

3% of scientists in this discipline score the same or lower.

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

Overview

Alexis Conneau is a researcher affiliated with Facebook in the United States, specializing in computer science with a strong focus on artificial intelligence. Their research primarily addresses topics related to speech recognition and synthesis as well as natural language processing techniques.

Their recent publications demonstrate contributions to various aspects of speech and language technologies, including representation learning and few-shot learning evaluations. Notable papers include:

  • "XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale," 2022, Interspeech 2022
  • "Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning," 2020, arXiv (Cornell University)
  • "FLEURS: FEW-Shot Learning Evaluation of Universal Representations of Speech," 2023, 2022 IEEE Spoken Language Technology Workshop (SLT)
  • "Scaling Speech Technology to 1,000+ Languages," 2023, arXiv (Cornell University)
  • "GPT-4o System Card," 2024, arXiv (Cornell University)

Alexis Conneau frequently collaborates with several other researchers, including Michael Auli, Alexei Baevski, Ankur Bapna, Andros Tjandra, and Jason Riesa. These collaborations have led to numerous joint publications that span multiple venues.

Their work has appeared extensively in publication venues such as:

  • arXiv (Cornell University), with 20 publications
  • Interspeech 2022, with 3 publications
  • 2022 IEEE Spoken Language Technology Workshop (SLT), with 1 publication
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), with 1 publication

The main fields of study for Alexis Conneau include computer science, with specialized research in artificial intelligence, signal processing, and computer vision and pattern recognition. Their work covers significant subfields and topics such as:

  • Artificial Intelligence
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Speech Recognition and Synthesis
  • Natural Language Processing Techniques
  • Topic Modeling
  • Music and Audio Processing
  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Speech and Audio Processing

Best Publications

  • Unsupervised Cross-lingual Representation Learning at Scale

    Alexis Conneau;Kartikay Khandelwal;Naman Goyal;Vishrav Chaudhary

  • Supervised learning of universal sentence representations from natural language inference data

    Alexis Conneau;Douwe Kiela;Holger Schwenk;Loïc Barrault

  • Cross-lingual Language Model Pretraining

    Alexis Conneau;Guillaume Lample

  • Word translation without parallel data

    Guillaume Lample;Alexis Conneau;Marc'Aurelio Ranzato;Ludovic Denoyer

  • Very deep convolutional networks for text classification

    Alexis Conneau;Holger Schwenk;Loïc Barrault;Yann Lecun

  • XNLI: Evaluating Cross-lingual Sentence Representations

    Alexis Conneau;Ruty Rinott;Guillaume Lample;Adina Williams

  • What you can cram into a single \$&!#* vector: Probing sentence embeddings for linguistic properties

    Alexis Conneau;German Kruszewski;Guillaume Lample;Loïc Barrault

  • Phrase-Based & Neural Unsupervised Machine Translation

    Guillaume Lample;Myle Ott;Alexis Conneau;Ludovic Denoyer

  • Unsupervised Machine Translation Using Monolingual Corpora Only

    Guillaume Lample;Alexis Conneau;Ludovic Denoyer;Marc'Aurelio Ranzato

  • Unsupervised Cross-lingual Representation Learning for Speech Recognition

    Alexis Conneau;Alexei Baevski;Ronan Collobert;Abdelrahman Mohamed

  • SentEval: An Evaluation Toolkit for Universal Sentence Representations

    Alexis Conneau;Douwe Kiela

  • XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale

    Arun Babu;Changhan Wang;Andros Tjandra;Kushal Lakhotia

  • Word Translation Without Parallel Data

    Alexis Conneau;Guillaume Lample;Marc'Aurelio Ranzato;Ludovic Denoyer

  • CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

    Guillaume Wenzek;Marie-Anne Lachaux;Alexis Conneau;Vishrav Chaudhary

  • Very Deep Convolutional Networks for Natural Language Processing.

    Alexis Conneau;Holger Schwenk;Loïc Barrault;Yann LeCun

  • Meta-Prod2Vec: Product Embeddings Using Side-Information for Recommendation

    Flavian Vasile;Elena Smirnova;Alexis Conneau

  • XNLI: Evaluating Cross-lingual Sentence Representations

    Alexis Conneau;Guillaume Lample;Ruty Rinott;Adina Williams

  • Emerging Cross-lingual Structure in Pretrained Language Models

    Alexis Conneau;Shijie Wu;Haoran Li;Luke Zettlemoyer

  • FLEURS: FEW-Shot Learning Evaluation of Universal Representations of Speech

    Unknown

  • Unsupervised Machine Translation Using Monolingual Corpora Only

    Guillaume Lample;Alexis Conneau;Ludovic Denoyer;Marc'Aurelio Ranzato

  • Self-training Improves Pre-training for Natural Language Understanding

    Jingfei Du;Edouard Grave;Beliz Gunel;Vishrav Chaudhary

  • Emerging Cross-lingual Structure in Pretrained Language Models

    Shijie Wu;Alexis Conneau;Haoran Li;Luke Zettlemoyer

Frequent Co-Authors

Michael Auli
Michael Auli Facebook (United States)
Veselin Stoyanov
Veselin Stoyanov Facebook (United States)
Holger Schwenk
Holger Schwenk Facebook (United States)
Ludovic Denoyer
Ludovic Denoyer Sorbonne University
Myle Ott
Myle Ott Facebook (United States)
Douwe Kiela
Douwe Kiela Stanford University
Edouard Grave
Edouard Grave Facebook (United States)
Marc'Aurelio Ranzato
Marc'Aurelio Ranzato DeepMind (United Kingdom)
Juan Pino
Juan Pino Facebook (United States)
Ronan Collobert
Ronan Collobert Facebook (United States)

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