Daniel Bruder
Impact in
- Control and Systems Engineering top 10%
- Robot Manipulation and Learning
- Iterative Learning Control Systems
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- Model Reduction and Neural Networks
Papers in
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- Soft Robotics and Applications 8
- Advanced Sensor and Energy Harvesting Materials 3
- Prosthetics and Rehabilitation Robotics 2
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- Micro and Nano Robotics 4
- Co-authors
- Ram Vasudevan (4 shared papers)R. Brent Gillespie (3 shared papers)C. David Remy (3 shared papers)Robert J. Wood (3 shared papers)Joshua Bishop-Moser (3 shared papers)Sridhar Kota (3 shared papers)Clark B. Teeple (1 shared paper)Moritz A. Graule (1 shared paper)
- Journals
- The International Journal of Robotics Research (2 papers)IEEE Transactions on Robotics (1 paper)IEEE Robotics and Automation Letters (1 paper)Journal of Mechanisms and Robotics (1 paper)Science Robotics (1 paper)
- Partner nations
- United StatesGermany
In The Last Decade
Daniel Bruder
10 papers receiving 279 citations
Daniel Bruder's Hit Papers
Peers
Comparison fields: 5 of 39
- Control and Systems Engineering 136
- Statistical and Nonlinear Physics 66
- Biomedical Engineering 173
- Condensed Matter Physics 43
- Mechanical Engineering 67
Countries citing papers authored by Daniel Bruder
This map shows the geographic impact of Daniel Bruder'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 Daniel Bruder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Bruder more than expected).
Fields of papers citing papers by Daniel Bruder
This network shows the impact of papers produced by Daniel Bruder. 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 Daniel Bruder. The network helps show where Daniel Bruder may publish in the future.
Co-authors
The 11 scholars most cited alongside Daniel Bruder, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Data-Driven Control of Soft Robots Using Koopman Operator Theory Hit paper breakdown → | 2020 | 178 |
| 2 | 2018 | 36 | |
| 3 | 2023 | 31 | |
| 4 | 2021 | 10 | |
| 5 | 2017 | 9 | |
| 6 | 2017 | 5 | |
| 7 | 2022 | 5 | |
| 8 | 2024 | 5 | |
| 9 | 2023 | 2 | |
| 10 | 2024 | 1 |
About Daniel Bruder
Daniel Bruder is a scholar working on Biomedical Engineering, Condensed Matter Physics, Control and Systems Engineering, Statistical and Nonlinear Physics and Computational Mechanics, having authored 10 papers that have together received 282 indexed citations. Recurring topics across this work include Soft Robotics and Applications (8 papers), Micro and Nano Robotics (4 papers), Advanced Sensor and Energy Harvesting Materials (3 papers), Robot Manipulation and Learning (2 papers), Prosthetics and Rehabilitation Robotics (2 papers), Lattice Boltzmann Simulation Studies (2 papers), Model Reduction and Neural Networks (2 papers) and Advanced Materials and Mechanics (1 paper). The work is most often cited by research in Control and Systems Engineering (136 citations), Statistical and Nonlinear Physics (66 citations), Biomedical Engineering (173 citations), Condensed Matter Physics (43 citations) and Mechanical Engineering (67 citations). Daniel Bruder has collaborated with scholars based in United States and Germany. Frequent co-authors include Ram Vasudevan, R. Brent Gillespie, C. David Remy, Robert J. Wood, Joshua Bishop-Moser, Sridhar Kota, Clark B. Teeple, Moritz A. Graule, R.J.K. Wood and Keith W. Buffinton. Their work appears in journals such as The International Journal of Robotics Research, IEEE Transactions on Robotics, IEEE Robotics and Automation Letters, Journal of Mechanisms and Robotics and Science Robotics.
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.