Johannes A. Stork

1.5k total citations
44 papers, 930 citations indexed

About

Johannes A. Stork is a scholar working on Control and Systems Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Johannes A. Stork has authored 44 papers receiving a total of 930 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Control and Systems Engineering, 19 papers in Artificial Intelligence and 18 papers in Computer Vision and Pattern Recognition. Recurrent topics in Johannes A. Stork's work include Robot Manipulation and Learning (26 papers), Reinforcement Learning in Robotics (13 papers) and Human Pose and Action Recognition (7 papers). Johannes A. Stork is often cited by papers focused on Robot Manipulation and Learning (26 papers), Reinforcement Learning in Robotics (13 papers) and Human Pose and Action Recognition (7 papers). Johannes A. Stork collaborates with scholars based in Sweden, United States and Germany. Johannes A. Stork's co-authors include Danica Kragić, Kai O. Arras, Kaiyu Hang, Gian Diego Tipaldi, Matthias Luber, Todor Stoyanov, Florian T. Pokorny, Luciano Spinello, Weihao Yuan and Yasemin Bekiroglu and has published in prestigious journals such as IEEE Transactions on Robotics, Neural Computing and Applications and Robotics and Autonomous Systems.

In The Last Decade

Johannes A. Stork

41 papers receiving 906 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Johannes A. Stork Sweden 16 462 432 272 259 120 44 930
Garrett Warnell United States 17 181 0.4× 435 1.0× 247 0.9× 112 0.4× 180 1.5× 50 802
Xuesu Xiao United States 20 254 0.5× 680 1.6× 273 1.0× 165 0.6× 384 3.2× 81 1.1k
Glen Berseth Canada 15 519 1.1× 430 1.0× 332 1.2× 415 1.6× 54 0.5× 39 1.1k
Dimitrios Kanoulas United Kingdom 17 420 0.9× 340 0.8× 152 0.6× 343 1.3× 157 1.3× 74 827
Jeremy Ma United States 15 300 0.6× 350 0.8× 162 0.6× 196 0.8× 221 1.8× 21 757
Paulo Costa Portugal 14 365 0.8× 397 0.9× 128 0.5× 142 0.5× 312 2.6× 145 980
Masafumi Hashimoto Japan 13 214 0.5× 343 0.8× 204 0.8× 95 0.4× 163 1.4× 143 834
Songmin Jia China 15 228 0.5× 445 1.0× 105 0.4× 186 0.7× 279 2.3× 140 917
W.S. Wijesoma Singapore 16 382 0.8× 518 1.2× 269 1.0× 146 0.6× 432 3.6× 67 1.2k
James Bruce United States 10 334 0.7× 703 1.6× 247 0.9× 150 0.6× 397 3.3× 16 1.0k

Countries citing papers authored by Johannes A. Stork

Since Specialization
Citations

This map shows the geographic impact of Johannes A. Stork'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 Johannes A. Stork with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johannes A. Stork more than expected).

Fields of papers citing papers by Johannes A. Stork

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Johannes A. Stork. 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 Johannes A. Stork. The network helps show where Johannes A. Stork may publish in the future.

Co-authorship network of co-authors of Johannes A. Stork

This figure shows the co-authorship network connecting the top 25 collaborators of Johannes A. Stork. A scholar is included among the top collaborators of Johannes A. Stork 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 Johannes A. Stork. Johannes A. Stork 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.
Schaffernicht, Erik, et al.. (2025). Predict-and-Optimize Techniques for Data-Driven Optimization Problems: A Review. Neural Processing Letters. 57(2). 1 indexed citations
2.
Magnusson, Martin, et al.. (2024). Learning Extrinsic Dexterity with Parameterized Manipulation Primitives. Örebro University Library (Örebro University). 5404–5410. 5 indexed citations
3.
Stork, Johannes A., et al.. (2024). Tracking Branched Deformable Linear Objects Using Particle Filtering on Depth Images. Örebro University Library (Örebro University). 912–919. 1 indexed citations
4.
Stoyanov, Todor, et al.. (2022). Online Distance Field Priors for Gaussian Process Implicit Surfaces. IEEE Robotics and Automation Letters. 7(4). 8996–9003. 7 indexed citations
5.
Stork, Johannes A., et al.. (2022). MPR-RL: Multi-Prior Regularized Reinforcement Learning for Knowledge Transfer. IEEE Robotics and Automation Letters. 7(3). 7652–7659. 6 indexed citations
6.
Stork, Johannes A., et al.. (2022). Online Model Learning for Shape Control of Deformable Linear Objects. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 4056–4062. 6 indexed citations
7.
Topp, Elin Anna, et al.. (2022). Variable Impedance Skill Learning for Contact-Rich Manipulation. IEEE Robotics and Automation Letters. 7(3). 8391–8398. 12 indexed citations
8.
Stork, Johannes A., et al.. (2022). A Stack-of-Tasks Approach Combined With Behavior Trees: A New Framework for Robot Control. IEEE Robotics and Automation Letters. 7(4). 12110–12117. 8 indexed citations
9.
Stork, Johannes A., et al.. (2022). Visual state estimation in unseen environments through domain adaptation and metric learning. Frontiers in Robotics and AI. 9. 833173–833173. 1 indexed citations
10.
Stork, Johannes A., et al.. (2022). Context-Aware Grasp Generation in Cluttered Scenes. 2022 International Conference on Robotics and Automation (ICRA). 1492–1498. 21 indexed citations
11.
Magg, Sven, et al.. (2022). Hierarchical goals contextualize local reward decomposition explanations. Neural Computing and Applications. 35(23). 16693–16704. 8 indexed citations
12.
Yuan, Weihao, et al.. (2020). Multi-Object Rearrangement with Monte Carlo Tree Search: A Case Study on Planar Nonprehensile Sorting. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 9433–9440. 39 indexed citations
13.
Antonova, Rika, et al.. (2018). Global Search with Bernoulli Alternation Kernel for Task-oriented Grasping Informed by Simulation. KTH Publication Database DiVA (KTH Royal Institute of Technology). 87. 641–650. 4 indexed citations
14.
Bekiroglu, Yasemin, Andreas Damianou, Renaud Detry, et al.. (2016). Probabilistic consolidation of grasp experience. Explore Bristol Research. 193–200. 9 indexed citations
15.
Hang, Kaiyu, Miao Li, Johannes A. Stork, et al.. (2014). Hierarchical Fingertip Space for Synthesizing Adaptable Fingertip Grasps. Chalmers Research (Chalmers University of Technology). 2 indexed citations
16.
Stork, Johannes A., et al.. (2014). Cooperative grasping through topological object representation. 29. 685–692. 2 indexed citations
17.
Stork, Johannes A., Florian T. Pokorny, & Danica Kragić. (2013). Towards Postural Synergies for Caging Grasps. International Conference on Robotics and Automation. 1 indexed citations
18.
Stork, Johannes A., et al.. (2012). Audio-based human activity recognition using Non-Markovian Ensemble Voting. 509–514. 77 indexed citations
19.
Stork, Johannes A., et al.. (2011). Audio-Based Human Activity Recognition with Robots. 1 indexed citations
20.
Luber, Matthias, Johannes A. Stork, Gian Diego Tipaldi, & Kai O. Arras. (2010). People tracking with human motion predictions from social forces. 464–469. 207 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.

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