2026 Matthias Hein: Engineering and Technology Researcher – H-Index, Publications & Awards

D-Index & Metrics

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Engineering and Technology	64	1623	1544	46	46	557	16984

Discipline name

D-Index

World Ranking

Current World Ranking

National Ranking

Current National Ranking

Publications

Citations

Engineering and Technology

1623

1544

557

16984

Engineering and Technology

D-Index

Citations

16984

World Ranking

1623

National Ranking

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

819
Citations
Latent Embeddings for Zero-Shot Classification

Yongqin Xian;Zeynep Akata;Gaurav Sharma;Quynh Nguyen

769
Citations
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks

Francesco Croce;Matthias Hein

636
Citations
Square Attack: A Query-Efficient Black-Box Adversarial Attack via Random Search

Maksym Andriushchenko;Francesco Croce;Nicolas Flammarion;Matthias Hein

599
Citations
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

425
Citations
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation

Matthias Hein;Maksym Andriushchenko

389
Citations
From graphs to manifolds – weak and strong pointwise consistency of graph laplacians

Matthias Hein;Jean-Yves Audibert;Ulrike von Luxburg

386
Citations
Spectral clustering based on the graph p-Laplacian

Thomas Bühler;Matthias Hein

352
Citations
Graph Laplacians and their Convergence on Random Neighborhood Graphs

Matthias Hein;Jean-Yves Audibert;Ulrike von Luxburg

307
Citations
Intrinsic dimensionality estimation of submanifolds in Rd

Matthias Hein;Jean-Yves Audibert

259
Citations
An Eigen-Analysis of Compact Antenna Arrays and Its Application to Port Decoupling

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

254
Citations
Manifold Denoising

Matthias Hein;Markus Maier

235
Citations
An integer linear programming approach for finding deregulated subgraphs in regulatory networks

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

234
Citations
Variants of RMSProp and Adagrad with logarithmic regret bounds

Mahesh Chandra Mukkamala;Matthias Hein

233
Citations
Non-negative least squares for high-dimensional linear models: Consistency and sparse recovery without regularization

Martin Slawski;Matthias Hein

229
Citations
The loss surface of deep and wide neural networks

Quynh Nguyen;Matthias Hein

229
Citations
Disentangling Adversarial Robustness and Generalization

David Stutz;Matthias Hein;Bernt Schiele

223
Citations
Hilbertian Metrics and Positive Definite Kernels on Probability Measures

Matthias Hein;Olivier Bousquet

218
Citations
Influence of graph construction on graph-based clustering measures

Markus Maier;Ulrike V. Luxburg;Matthias Hein

217
Citations
Miniaturized antenna arrays using decoupling networks with realistic elements

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

210
Citations
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks

Agustinus Kristiadi;Matthias Hein;Philipp Hennig

93
Citations
RobustBench: a standardized adversarial robustness benchmark.

Francesco Croce;Maksym Andriushchenko;Vikash Sehwag;Edoardo Debenedetti

82
Citations