World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
11944
World Ranking
7053
National Ranking
155

Eric Gaussier 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 Eric Gaussier 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: 251 publications — 63rd percentile

63% of scientists in this discipline score the same or lower.

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

Eric Gaussier 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 Eric Gaussier 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: 45 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Overview

Eric Gaussier is affiliated with Grenoble Alpes University in France, contributing to the field of Computer Science with a focus on Artificial Intelligence and related subfields. Their research output includes work in Computer Vision and Pattern Recognition, Signal Processing, Computational Theory and Mathematics, and Management Science and Operations Research.

The scientist's work encompasses several main topics including:

  • Topic Modeling
  • Bayesian Modeling and Causal Inference
  • Natural Language Processing Techniques
  • Text and Document Classification Technologies
  • Rough Sets and Fuzzy Logic
  • Time Series Analysis and Forecasting
  • Advanced Graph Neural Networks

Among recent publications by Eric Gaussier are the following papers:

  • Survey and Evaluation of Causal Discovery Methods for Time Series, 2022, Journal of Artificial Intelligence Research
  • Deep k-Means: Jointly clustering with k-Means and learning representations, 2020, Pattern Recognition Letters
  • Heavy-tailed Representations, Text Polarity Classification & Data Augmentation, 2020, arXiv (Cornell University)
  • The Power of Selecting Key Blocks with Local Pre-ranking for Long Document Information Retrieval, 2022, ACM Transactions on Information Systems
  • Entropy-Based Discovery of Summary Causal Graphs in Time Series, 2022, Entropy

Eric Gaussier frequently collaborates with other researchers. The most frequent co-authors include:

  • Émilie Devijver
  • Karim ASSAAD
  • Minghan Li
  • Diana Nicoleta Popa
  • Thibaut Thonet

Their work is often published in venues such as:

  • Harvard Dataverse
  • arXiv (Cornell University)
  • Entropy
  • Natural Language Engineering
  • HAL (Le Centre pour la Communication Scientifique Directe)

Best Publications

  • A probabilistic interpretation of precision, recall and F -score, with implication for evaluation

    Cyril Goutte;Eric Gaussier

  • Complex embeddings for simple link prediction

    Théo Trouillon;Johannes Welbl;Sebastian Riedel;Éric Gaussier

  • An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition

    George Tsatsaronis;Georgios Balikas;Prodromos Malakasiotis;Ioannis Partalas

  • Relation between PLSA and NMF and implications

    Eric Gaussier;Cyril Goutte

  • Word sequence kernels

    Nicola Cancedda;Eric Gaussier;Cyril Goutte;Jean Michel Renders

  • Towards automatic extraction of monolingual and bilingual terminology

    Béatrice Daille;Éric Gaussier;Jean-Marc Langé

  • Deep k-Means: Jointly clustering with k-Means and learning representations

    Maziar Moradi Fard;Thibaut Thonet;Eric Gaussier

  • Grouping words with equivalent substrings by automatic clustering based on suffix relationships

    Eric Gaussier;Gregory Grefenstette;Jean-Pierre Chanod

  • Knowledge graph completion via complex tensor factorization

    Théo Trouillon;Christopher R. Dance;Éric Gaussier;Johannes Welbl

  • Apparatus and method for information retrieval

    Claude Roux;Denys Proux;Eric Gaussier

  • LSHTC: A Benchmark for Large-Scale Text Classification.

    Ioannis Partalas;Aris Kosmopoulos;Nicolas Baskiotis;Thierry Artières

  • Evaluation measures for hierarchical classification: a unified view and novel approaches

    Aris Kosmopoulos;Ioannis Partalas;Eric Gaussier;Georgios Paliouras

  • Information-based models for ad hoc IR

    Stéphane Clinchant;Eric Gaussier

  • A Geometric View on Bilingual Lexicon Extraction from Comparable Corpora

    Eric Gaussier;J.M. Renders;I. Matveeva;C. Goutte

  • Unsupervised learning of derivational morphology from inflectional lexicons

    Eric Gaussier

  • Method for aligning sentences at the word level enforcing selective contiguity constraints

    Madalina Barbaiani;Nicola Cancedda;Christopher R. Dance;Szilard Zsolt Fazekas

  • An approach based on multilingual thesauri and model combination for bilingual lexicon extraction

    Hervé Déjean;Éric Gaussier;Fatia Sadat

  • Adaptive spam message detector

    Cyril Goutte;Pierre Isabelle;Eric Gaussier;Stephen Kruger

  • Improving backfilling by using machine learning to predict running times

    Eric Gaussier;David Glesser;Valentin Reis;Denis Trystram

  • Improving Corpus Comparability for Bilingual Lexicon Extraction from Comparable Corpora

    Bo Li;Eric Gaussier

  • Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing

    Dan Jurafsky;Eric Gaussier

  • Knowledge Graph Completion via Complex Tensor Factorization

    Théo Trouillon;Christopher R. Dance;Johannes Welbl;Sebastian Riedel

Frequent Co-Authors

Cyril Goutte
Cyril Goutte National Research Council Canada
Gregory Grefenstette
Gregory Grefenstette Florida Institute for Human and Machine Cognition
Ion Androutsopoulos
Ion Androutsopoulos Athens University of Economics and Business
Patrick Gallinari
Patrick Gallinari Sorbonne University
Francine R. Chen
Francine R. Chen FX Palo Alto Laboratory
Sebastian Riedel
Sebastian Riedel University College London
Sihem Amer-Yahia
Sihem Amer-Yahia Grenoble Alpes University
Axel-Cyrille Ngonga Ngomo
Axel-Cyrille Ngonga Ngomo University of Paderborn
Georgios Paliouras
Georgios Paliouras National Centre of Scientific Research Demokritos
George Tsatsaronis
George Tsatsaronis Technical University of Berlin

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