Markus Wulfmeier

1.3k total citations
10 papers, 232 citations indexed

About

Markus Wulfmeier is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Civil and Structural Engineering. According to data from OpenAlex, Markus Wulfmeier has authored 10 papers receiving a total of 232 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 2 papers in Civil and Structural Engineering. Recurrent topics in Markus Wulfmeier's work include Reinforcement Learning in Robotics (5 papers), Adversarial Robustness in Machine Learning (3 papers) and Soil Mechanics and Vehicle Dynamics (2 papers). Markus Wulfmeier is often cited by papers focused on Reinforcement Learning in Robotics (5 papers), Adversarial Robustness in Machine Learning (3 papers) and Soil Mechanics and Vehicle Dynamics (2 papers). Markus Wulfmeier collaborates with scholars based in United Kingdom, United States and Netherlands. Markus Wulfmeier's co-authors include Ingmar Posner, Peter Ondrúška, Dominic Zeng Wang, Dushyant Rao, Alex Bewley, Carmine Senatore, Karl Iagnemma, José E. Andrade, Ivan Vlahinić and Paramsothy Jayakumar and has published in prestigious journals such as The International Journal of Robotics Research, SAE technical papers on CD-ROM/SAE technical paper series and Journal of Terramechanics.

In The Last Decade

Markus Wulfmeier

10 papers receiving 225 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Markus Wulfmeier United Kingdom 5 82 79 67 56 43 10 232
Yasutomo Kawanishi Japan 9 75 0.9× 236 3.0× 37 0.6× 14 0.3× 31 0.7× 93 355
Siyuan Liang China 6 44 0.5× 114 1.4× 28 0.4× 13 0.2× 13 0.3× 14 269
Hanting Yang Japan 5 28 0.3× 87 1.1× 82 1.2× 32 0.6× 8 0.2× 10 273
Dmitry Yudin Russia 8 33 0.4× 123 1.6× 39 0.6× 21 0.4× 11 0.3× 45 223
Yuxiao Zhang Japan 3 28 0.3× 80 1.0× 83 1.2× 32 0.6× 7 0.2× 9 253
Peide Cai Hong Kong 9 65 0.8× 195 2.5× 148 2.2× 57 1.0× 30 0.7× 12 326
Daniel Göhring Germany 6 44 0.5× 73 0.9× 63 0.9× 37 0.7× 6 0.1× 13 203
Jyh-Jing Hwang United States 9 120 1.5× 179 2.3× 17 0.3× 14 0.3× 91 2.1× 12 308
Dhiraj Gandhi United States 6 88 1.1× 137 1.7× 42 0.6× 48 0.9× 13 0.3× 7 249
Dong Seop Han China 10 46 0.6× 91 1.2× 7 0.1× 60 1.1× 25 0.6× 21 287

Countries citing papers authored by Markus Wulfmeier

Since Specialization
Citations

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

Fields of papers citing papers by Markus Wulfmeier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Markus Wulfmeier. 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 Markus Wulfmeier. The network helps show where Markus Wulfmeier may publish in the future.

Co-authorship network of co-authors of Markus Wulfmeier

This figure shows the co-authorship network connecting the top 25 collaborators of Markus Wulfmeier. A scholar is included among the top collaborators of Markus Wulfmeier 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 Markus Wulfmeier. Markus Wulfmeier is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
1.
Lampe, Thomas, Abbas Abdolmaleki, Sandy H. Huang, et al.. (2024). Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots. 5. 7772–7779. 1 indexed citations
2.
Wulfmeier, Markus, Dushyant Rao, Roland Hafner, et al.. (2021). Data-efficient Hindsight Off-policy Option Learning. arXiv (Cornell University). 11340–11350. 3 indexed citations
3.
Rao, Dushyant, et al.. (2019). Attention Privileged Reinforcement Learning for Domain Transfer. arXiv (Cornell University). 1 indexed citations
4.
Wulfmeier, Markus, et al.. (2018). TACO: Learning Task Decomposition via Temporal Alignment for Control. Oxford University Research Archive (ORA) (University of Oxford). 4654–4663. 2 indexed citations
5.
Wulfmeier, Markus, Alex Bewley, & Ingmar Posner. (2017). Incremental Adversarial Domain Adaptation.. arXiv (Cornell University). 1 indexed citations
6.
Wulfmeier, Markus, Alex Bewley, & Ingmar Posner. (2017). Addressing appearance change in outdoor robotics with adversarial domain adaptation. Oxford University Research Archive (ORA) (University of Oxford). 1551–1558. 33 indexed citations
7.
Wulfmeier, Markus, Dushyant Rao, Dominic Zeng Wang, Peter Ondrúška, & Ingmar Posner. (2017). Large-scale cost function learning for path planning using deep inverse reinforcement learning. The International Journal of Robotics Research. 36(10). 1073–1087. 123 indexed citations
8.
Wulfmeier, Markus, Peter Ondrúška, & Ingmar Posner. (2015). Deep Inverse Reinforcement Learning.. arXiv (Cornell University). 21 indexed citations
9.
Senatore, Carmine, Markus Wulfmeier, Ivan Vlahinić, José E. Andrade, & Karl Iagnemma. (2013). Design and implementation of a particle image velocimetry method for analysis of running gear–soil interaction. Journal of Terramechanics. 50(5-6). 311–326. 32 indexed citations
10.
Senatore, Carmine, et al.. (2012). INVESTIGATION OF STRESS AND FAILURE IN GRANULAR SOILS FOR LIGHTWEIGHT ROBOTIC VEHICLE APPLICATIONS. SAE technical papers on CD-ROM/SAE technical paper series. 1. 15 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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2026