2026 Jürgen Schmidhuber: 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	113	194	189	1	1	530	230372

Research.com Recognitions

2026 - Research.com Computer Science in Saudi Arabia Leader Award
2025 - Research.com Computer Science in Saudi Arabia Leader Award
2023 - Research.com Computer Science in Switzerland Leader Award
2022 - Research.com Computer Science in Switzerland Leader Award

Overview

Jürgen Schmidhuber is affiliated with King Abdullah University of Science and Technology in Saudi Arabia. Their research contributions primarily span the field of Computer Science, with a strong focus on Artificial Intelligence and related subfields.

Their work covers several subfields of study, including:

Artificial Intelligence
Computer Vision and Pattern Recognition
Signal Processing
Electrical and Electronic Engineering
Management Science and Operations Research

Core topics in their research include:

Reinforcement Learning in Robotics
Topic Modeling
Neural Networks and Applications
Natural Language Processing Techniques
Multimodal Machine Learning Applications
Domain Adaptation and Few-Shot Learning
Explainable Artificial Intelligence (XAI)

Frequent co-authors in their collaborative work consist of:

Kazuki Irie
Francesco Faccio
Róbert Csordás
Dylan R. Ashley
Louis Kirsch

The venues most often featuring their publications include:

arXiv (Cornell University)
Neural Computation
Zenodo (CERN European Organization for Nuclear Research)
Neural Networks
Proceedings of the AAAI Conference on Artificial Intelligence

Selected recent papers by Jürgen Schmidhuber demonstrate a focus on neural network theory and generative models:

Generative Adversarial Networks are special cases of Artificial Curiosity (1990) and also closely related to Predictability Minimization (1991), 2020, Neural Networks
On the Binding Problem in Artificial Neural Networks, 2020, arXiv (Cornell University)
Reagent prediction with a molecular transformer improves reaction data quality, 2023, Chemical Science
Investigating object compositionality in Generative Adversarial Networks, 2020, Neural Networks
Linear Transformers Are Secretly Fast Weight Programmers, 2021, arXiv (Cornell University)

Best Publications

Long short-term memory

Sepp Hochreiter;Jürgen Schmidhuber

106245
Citations
Deep learning in neural networks

Jürgen Schmidhuber

26211
Citations
Learning to Forget: Continual Prediction with LSTM

Felix A. Gers;Jürgen A. Schmidhuber;Fred A. Cummins

7582
Citations
LSTM: A Search Space Odyssey

Klaus Greff;Rupesh K. Srivastava;Jan Koutnik;Bas R. Steunebrink

7331
Citations
Multi-column deep neural networks for image classification

Dan Cireşan;Ueli Meier;Juergen Schmidhuber

6139
Citations
Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks

Alex Graves;Santiago Fernández;Faustino Gomez;Jürgen Schmidhuber

5926
Citations
Learning to forget: continual prediction with LSTM

F.A. Gers;J. Schmidhuber;F. Cummins

4890
Citations
2005 Special Issue: Framewise phoneme classification with bidirectional LSTM and other neural network architectures

Alex Graves;Jürgen Schmidhuber

4745
Citations
Framewise phoneme classification with bidirectional LSTM and other neural network architectures

Alex Graves;Jürgen Schmidhuber

3516
Citations
A Novel Connectionist System for Unconstrained Handwriting Recognition

A. Graves;M. Liwicki;S. Fernandez;R. Bertolami

2569
Citations
Stacked convolutional auto-encoders for hierarchical feature extraction

Jonathan Masci;Ueli Meier;Dan Cireşan;Jürgen Schmidhuber

2425
Citations
Mitosis detection in breast cancer histology images with deep neural networks.

Dan Claudio Ciresan;Alessandro Giusti;Luca Maria Gambardella;Juergen Schmidhuber

1836
Citations
Flexible, high performance convolutional neural networks for image classification

Dan C. Cireşan;Ueli Meier;Jonathan Masci;Luca M. Gambardella

1820
Citations
Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images

Dan Ciresan;Alessandro Giusti;Luca M. Gambardella;Jürgen Schmidhuber

1814
Citations
Learning precise timing with lstm recurrent networks

Felix A. Gers;Nicol N. Schraudolph;Jürgen Schmidhuber

1583
Citations
Deep, big, simple neural nets for handwritten digit recognition

Dan Claudiu Cireşan;Ueli Meier;Luca Maria Gambardella;Jürgen Schmidhuber

1488
Citations
Training very deep networks

Rupesh Kumar Srivastava;Klaus Greff;Jürgen Schmidhuber

1347
Citations
2012 Special Issue: Multi-column deep neural network for traffic sign classification

Dan CireşAn;Ueli Meier;Jonathan Masci;JüRgen Schmidhuber

1338
Citations
Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks

Alex Graves;Jürgen Schmidhuber

1223
Citations
Modeling Attacks on Physical Unclonable Functions.

Ulrich Rührmair;Frank Sehnke;Jan Sölter;Gideon Dror

1168
Citations

Frequent Co-Authors

Alex Graves Google (United States)

Tom Schaul DeepMind (United Kingdom)

Daan Wierstra DeepMind (United Kingdom)

Luca Maria Gambardella Dalle Molle Institute for Artificial Intelligence Research

Marco Wiering University of Groningen

Julian Togelius New York University

Douglas Eck Google (United States)

Sepp Hochreiter Johannes Kepler University of Linz

Michael Wand Johannes Gutenberg University of Mainz

Jan Peters Technical University of Darmstadt

External Links

Wikipedia of Jürgen Schmidhuber Personal website of Jürgen Schmidhuber Google Scholar page

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