World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
64
Citations
16984
World Ranking
1625
National Ranking
45

Matthias Hein publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Matthias Hein sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 557 publications — 96th percentile

96% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Matthias Hein D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Matthias Hein sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 64 D-Index — 84th percentile

84% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Matthias Hein is affiliated with the University of Tübingen in Germany. Their research activity spans various domains primarily within computer science and engineering, with a strong focus on artificial intelligence and its applications.

The main fields of study covered in Hein's publications include:

  • Computer Science
  • Engineering

Their work delves into several subfields, notably:

  • Artificial Intelligence
  • Aerospace Engineering
  • Electrical and Electronic Engineering
  • Radiology, Nuclear Medicine and Imaging
  • Computer Vision and Pattern Recognition

Key research topics associated with Hein involve:

  • Adversarial Robustness in Machine Learning
  • Anomaly Detection Techniques and Applications
  • COVID-19 diagnosis using AI
  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications
  • Antenna Design and Analysis
  • Medical Imaging Techniques and Applications

Hein has an extensive publication record with frequent appearances in the following venues:

  • arXiv (Cornell University)
  • 2022 16th European Conference on Antennas and Propagation (EuCAP)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Applied Sciences
  • Lecture notes in computer science

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

  • Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks, 2020, arXiv (Cornell University)
  • RobustBench: a standardized adversarial robustness benchmark, 2020, arXiv (Cornell University)
  • Sparse-RS: A Versatile Framework for Query-Efficient Sparse Black-Box Adversarial Attacks, 2022, Proceedings of the AAAI Conference on Artificial Intelligence
  • Square Attack: A Query-Efficient Black-Box Adversarial Attack via Random Search, 2020, Lecture notes in computer science
  • Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks, 2020, arXiv (Cornell University)

Hein frequently collaborates with the following researchers:

  • Francesco Croce
  • Christian Bornkessel
  • Valentyn Boreiko
  • Maximilian Augustin
  • Naman Deep Singh

Best Publications

  • Simple Does It: Weakly Supervised Instance and Semantic Segmentation

    Anna Khoreva;Rodrigo Benenson;Jan Hosang;Matthias Hein

  • Latent Embeddings for Zero-Shot Classification

    Yongqin Xian;Zeynep Akata;Gaurav Sharma;Quynh Nguyen

  • Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks

    Francesco Croce;Matthias Hein

  • Square Attack: A Query-Efficient Black-Box Adversarial Attack via Random Search

    Maksym Andriushchenko;Francesco Croce;Nicolas Flammarion;Matthias Hein

  • Why ReLU Networks Yield High-Confidence Predictions Far Away From the Training Data and How to Mitigate the Problem

    Matthias Hein;Maksym Andriushchenko;Julian Bitterwolf

  • Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation

    Matthias Hein;Maksym Andriushchenko

  • From graphs to manifolds – weak and strong pointwise consistency of graph laplacians

    Matthias Hein;Jean-Yves Audibert;Ulrike von Luxburg

  • Spectral clustering based on the graph p-Laplacian

    Thomas Bühler;Matthias Hein

  • Graph Laplacians and their Convergence on Random Neighborhood Graphs

    Matthias Hein;Jean-Yves Audibert;Ulrike von Luxburg

  • Intrinsic dimensionality estimation of submanifolds in Rd

    Matthias Hein;Jean-Yves Audibert

  • An Eigen-Analysis of Compact Antenna Arrays and Its Application to Port Decoupling

    C. Volmer;J. Weber;R. Stephan;K. Blau

  • Manifold Denoising

    Matthias Hein;Markus Maier

  • An integer linear programming approach for finding deregulated subgraphs in regulatory networks

    Christina Backes;Alexander Rurainski;Gunnar W. Klau;Oliver Müller

  • Variants of RMSProp and Adagrad with logarithmic regret bounds

    Mahesh Chandra Mukkamala;Matthias Hein

  • Non-negative least squares for high-dimensional linear models: Consistency and sparse recovery without regularization

    Martin Slawski;Matthias Hein

  • The loss surface of deep and wide neural networks

    Quynh Nguyen;Matthias Hein

  • Disentangling Adversarial Robustness and Generalization

    David Stutz;Matthias Hein;Bernt Schiele

  • Hilbertian Metrics and Positive Definite Kernels on Probability Measures

    Matthias Hein;Olivier Bousquet

  • Influence of graph construction on graph-based clustering measures

    Markus Maier;Ulrike V. Luxburg;Matthias Hein

  • Miniaturized antenna arrays using decoupling networks with realistic elements

    J. Weber;C. Volmer;K. Blau;R. Stephan

  • Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks

    Agustinus Kristiadi;Matthias Hein;Philipp Hennig

  • RobustBench: a standardized adversarial robustness benchmark.

    Francesco Croce;Maksym Andriushchenko;Vikash Sehwag;Edoardo Debenedetti

Frequent Co-Authors

Bernt Schiele
Bernt Schiele Max Planck Institute for Informatics
Oliver Ambacher
Oliver Ambacher University of Freiburg
Ulrike von Luxburg
Ulrike von Luxburg University of Tübingen
Rodrigo Benenson
Rodrigo Benenson Google (United States)
Robert Weigel
Robert Weigel University of Erlangen-Nuremberg
Olivier Bousquet
Olivier Bousquet Google (United States)
Bernhard Schölkopf
Bernhard Schölkopf Max Planck Institute for Intelligent Systems
Michael Lorenz
Michael Lorenz Leipzig University
Philipp Hennig
Philipp Hennig University of Tübingen
Joachim Weickert
Joachim Weickert Saarland University

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