Jochen J. Steil

4.8k total citations
175 papers, 3.1k citations indexed

About

Jochen J. Steil is a scholar working on Control and Systems Engineering, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Jochen J. Steil has authored 175 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 89 papers in Control and Systems Engineering, 75 papers in Artificial Intelligence and 46 papers in Biomedical Engineering. Recurrent topics in Jochen J. Steil's work include Robot Manipulation and Learning (78 papers), Neural Networks and Applications (41 papers) and Neural Networks and Reservoir Computing (24 papers). Jochen J. Steil is often cited by papers focused on Robot Manipulation and Learning (78 papers), Neural Networks and Applications (41 papers) and Neural Networks and Reservoir Computing (24 papers). Jochen J. Steil collaborates with scholars based in Germany, Japan and United Kingdom. Jochen J. Steil's co-authors include Matthias Rolf, Felix Reinhart, Michael Gienger, Helge Ritter, Klaus Neumann, Robert Haschke, Andre Lemme, Manuel Mühlig, Benjamin Schrauwen and Sebastian Wrede and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Transactions on Automatic Control.

In The Last Decade

Jochen J. Steil

170 papers receiving 3.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jochen J. Steil Germany 29 1.5k 1.3k 842 666 510 175 3.1k
Laxmidhar Behera India 33 1.7k 1.2× 625 0.5× 403 0.5× 507 0.8× 1000 2.0× 313 4.2k
Sukhan Lee South Korea 28 788 0.5× 535 0.4× 366 0.4× 542 0.8× 868 1.7× 258 3.8k
Rui Yan China 26 849 0.6× 479 0.4× 440 0.5× 375 0.6× 709 1.4× 139 2.4k
Majid Nili Ahmadabadi Iran 26 646 0.4× 482 0.4× 848 1.0× 305 0.5× 446 0.9× 202 2.4k
Marc Toussaint Germany 30 1.4k 0.9× 1.6k 1.3× 384 0.5× 504 0.8× 1.1k 2.2× 159 3.5k
Carme Torras Spain 32 1.9k 1.3× 868 0.7× 916 1.1× 299 0.4× 1.6k 3.2× 248 4.5k
Naoyuki Kubota Japan 23 1.1k 0.7× 945 0.7× 451 0.5× 282 0.4× 1.3k 2.5× 492 3.2k
Jun Nakanishi Japan 23 2.4k 1.6× 956 0.7× 1.9k 2.2× 396 0.6× 658 1.3× 64 3.5k
Sandra Hirche Germany 41 3.4k 2.3× 696 0.5× 1.0k 1.2× 1.0k 1.5× 568 1.1× 378 6.4k
Ludovic Righetti United States 34 1.8k 1.2× 511 0.4× 2.3k 2.8× 347 0.5× 403 0.8× 113 3.6k

Countries citing papers authored by Jochen J. Steil

Since Specialization
Citations

This map shows the geographic impact of Jochen J. Steil's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jochen J. Steil with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jochen J. Steil more than expected).

Fields of papers citing papers by Jochen J. Steil

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jochen J. Steil. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jochen J. Steil. The network helps show where Jochen J. Steil may publish in the future.

Co-authorship network of co-authors of Jochen J. Steil

This figure shows the co-authorship network connecting the top 25 collaborators of Jochen J. Steil. A scholar is included among the top collaborators of Jochen J. Steil based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jochen J. Steil. Jochen J. Steil is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Hoffman, Enrico Mingo, et al.. (2019). Compliant Humanoids Moving Toward Rehabilitation Applications: Transparent Integration of Real-Time Control, Whole-Body Motion Generation, and Virtual Reality. IEEE Robotics & Automation Magazine. 26(4). 83–93. 3 indexed citations
2.
Ötting, Sonja Kristine, et al.. (2017). Why criteria of decision fairness should be considered in robot design. PUB – Publications at Bielefeld University (Bielefeld University). 4 indexed citations
3.
Reinhart, Felix, et al.. (2016). Modelling of parameterized processes via regression in the model space.. PUB – Publications at Bielefeld University (Bielefeld University). 5 indexed citations
4.
Rolf, Matthias & Jochen J. Steil. (2013). Explorative learning of right inverse functions: theoretical implications of redundancy. PUB – Publications at Bielefeld University (Bielefeld University).
5.
Lemme, Andre, Klaus Neumann, Felix Reinhart, & Jochen J. Steil. (2013). Neurally Imprinted Stable Vector Fields. PUB – Publications at Bielefeld University (Bielefeld University). 332. 14 indexed citations
6.
Lemme, Andre, et al.. (2012). Learning visuo-motor coordination for pointing without depth calculation. PUB – Publications at Bielefeld University (Bielefeld University). 96. 3 indexed citations
7.
Neumann, Klaus & Jochen J. Steil. (2012). Intrinsic Plasticity via Natural Gradient Descent. The European Symposium on Artificial Neural Networks. 560. 4 indexed citations
8.
Reinhart, Felix & Jochen J. Steil. (2011). Reservoir regularization stabilizes learning of Echo State Networks with output feedback. PUB – Publications at Bielefeld University (Bielefeld University). 64. 9 indexed citations
9.
Wersing, Heiko, et al.. (2010). Figure-ground Segmentation using Metrics Adaptation in Level Set Methods. The European Symposium on Artificial Neural Networks. 37(11). 422–2582. 1 indexed citations
10.
Lemme, Andre, Felix Reinhart, & Jochen J. Steil. (2010). Efficient online learning of a non-negative sparse autoencoder. PUB – Publications at Bielefeld University (Bielefeld University). 18 indexed citations
11.
Belardinelli, Anna, Werner X. Schneider, & Jochen J. Steil. (2010). OOP: Object-Oriented-Priority for Motion Saliency Maps. Publikationen an der Universität Bielefeld (Universität Bielefeld). 381. 1 indexed citations
12.
Steil, Jochen J.. (2007). Several ways to solve the MSO problem.. The European Symposium on Artificial Neural Networks. 489–494. 9 indexed citations
13.
Steil, Jochen J., et al.. (2007). Intrinsic plasticity for reservoir learning algorithms.. The European Symposium on Artificial Neural Networks. 513–518. 10 indexed citations
14.
Steil, Jochen J. & Heiko Wersing. (2006). Recent Trends in Online Learning for Cognitive Robotics. PUB – Publications at Bielefeld University (Bielefeld University). 77–87. 2 indexed citations
15.
Steil, Jochen J.. (2005). Stability of backpropagation-decorrelation efficient O(N) recurrent learning.. The European Symposium on Artificial Neural Networks. 43–48. 9 indexed citations
16.
Steil, Jochen J.. (2002). Local structural stability of recurrent networks with time-varying weights. Neurocomputing. 48. 5 indexed citations
17.
Hammer, Barbara & Jochen J. Steil. (2002). Perspectives on learning with recurrent neural networks.. PUB – Publications at Bielefeld University (Bielefeld University). 357–368. 13 indexed citations
18.
Steil, Jochen J.. (2000). Local input-output stability of recurrent networks with time-varying weights. PUB – Publications at Bielefeld University (Bielefeld University). 281–286. 2 indexed citations
19.
Steil, Jochen J. & Helge Ritter. (1999). Maximisation of stability ranges for recurrent neural networks subject to on-line adaptation. PUB – Publications at Bielefeld University (Bielefeld University). 370–374. 3 indexed citations
20.
Steil, Jochen J. & Helge Ritter. (1998). Input-Output Stability of Recurrent Neural Networks with Delays using Circle Criteria. Natural Computing. 519–525. 5 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact

Rankless by CCL
2026