Martin Lawitzky
- Control and Systems Engineering top 5%
- Biomedical Engineering
- Mechanical Engineering
- Social Psychology top 10%
- Cognitive Neuroscience
- Co-authors
- Sandra HircheAlexander MörtlAyşe KüçükyılmazÇağatay BaşdoğanTevfik Metin SezginJosé Ramón MedinaDongheui LeeStefan M. Petters
- Topics
- Robot Manipulation and Learning (9 papers)Motor Control and Adaptation (4 papers)Teleoperation and Haptic Systems (4 papers)
- Journals
- The International Journal of Robotics ResearchKI - Künstliche Intelligenz2011 IEEE/RSJ International Conference on Intelligent Robots and Systems
In The Last Decade
Martin Lawitzky
11 papers receiving 428 citations
Peers
Comparison fields: 5 of 46
- Control and Systems Engineering 303
- Biomedical Engineering 156
- Mechanical Engineering 150
- Social Psychology 107
- Cognitive Neuroscience 103
Countries citing papers authored by Martin Lawitzky
This map shows the geographic impact of Martin Lawitzky'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 Martin Lawitzky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Lawitzky more than expected).
Fields of papers citing papers by Martin Lawitzky
This network shows the impact of papers produced by Martin Lawitzky. 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 Martin Lawitzky. The network helps show where Martin Lawitzky may publish in the future.
Co-authorship network of co-authors of Martin Lawitzky
This figure shows the co-authorship network connecting the top 25 collaborators of Martin Lawitzky. A scholar is included among the top collaborators of Martin Lawitzky 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 Martin Lawitzky. Martin Lawitzky is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 18 | |
| 3 | 17 | |
| 4 | 220 | |
| 5 | 13 | |
| 6 | 65 | |
| 7 | 13 | |
| 8 | 55 | |
| 9 | 19 | |
| 10 | 12 | |
| 11 | Integrating real time and power management in a real system | 12 |
About Martin Lawitzky
Martin Lawitzky is a scholar working on Control and Systems Engineering, Hardware and Architecture and Cognitive Neuroscience, having authored 11 papers that have together received 448 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (9 papers), Motor Control and Adaptation (4 papers) and Teleoperation and Haptic Systems (4 papers). The work is most often cited by research in Control and Systems Engineering (303 citations), Cognitive Neuroscience (103 citations) and Social Psychology (107 citations). Martin Lawitzky has collaborated with scholars based in Germany, Australia and Canada. Frequent co-authors include Sandra Hirche, Alexander Mörtl, Ayşe Küçükyılmaz, Çağatay Başdoğan, Tevfik Metin Sezgin, José Ramón Medina, Dongheui Lee, Stefan M. Petters, Adam Molin and Gordon Cheng. Their work appears in journals such as The International Journal of Robotics Research, KI - Künstliche Intelligenz and 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.
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.