Daniel Bruder

481 total citations · 1 hit paper
10 papers, 282 citations indexed

About

Daniel Bruder is a scholar working on Biomedical Engineering, Condensed Matter Physics and Control and Systems Engineering. According to data from OpenAlex, Daniel Bruder has authored 10 papers receiving a total of 282 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Biomedical Engineering, 4 papers in Condensed Matter Physics and 3 papers in Control and Systems Engineering. Recurrent topics in Daniel Bruder's work include Soft Robotics and Applications (8 papers), Micro and Nano Robotics (4 papers) and Advanced Sensor and Energy Harvesting Materials (3 papers). Daniel Bruder is often cited by papers focused on Soft Robotics and Applications (8 papers), Micro and Nano Robotics (4 papers) and Advanced Sensor and Energy Harvesting Materials (3 papers). Daniel Bruder collaborates with scholars based in United States and Germany. Daniel Bruder's co-authors include Ram Vasudevan, C. David Remy, R. Brent Gillespie, Robert J. Wood, Sridhar Kota, Joshua Bishop-Moser, Moritz A. Graule, Clark B. Teeple, R.J.K. Wood and Tianxiang Dai and has published in prestigious journals such as SHILAP Revista de lepidopterología, The International Journal of Robotics Research and IEEE Transactions on Robotics.

In The Last Decade

Daniel Bruder

10 papers receiving 279 citations

Hit Papers

Data-Driven Control of Soft Robots Using Koopman Operator... 2020 2026 2022 2024 2020 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Bruder United States 6 173 136 67 66 43 10 282
Ningning Song China 11 40 0.2× 184 1.4× 122 1.8× 31 0.5× 5 0.1× 25 310
Karthik Menon United States 10 45 0.3× 25 0.2× 27 0.4× 59 0.9× 60 1.4× 32 336
Aline Lefebvre-Lepot France 9 103 0.6× 21 0.2× 51 0.8× 26 0.4× 169 3.9× 25 315
Zbigniew Koruba Poland 9 22 0.1× 116 0.9× 42 0.6× 19 0.3× 4 0.1× 51 281
Sudhakar Nair United States 7 46 0.3× 11 0.1× 32 0.5× 7 0.1× 9 0.2× 15 214
Frederico Martins Alves da Silva Brazil 14 50 0.3× 229 1.7× 77 1.1× 45 0.7× 38 403
Marco Laudato Italy 7 37 0.2× 54 0.4× 66 1.0× 18 0.3× 1 0.0× 23 226
Claire Souilliez France 4 58 0.3× 168 1.2× 83 1.2× 12 0.2× 37 0.9× 5 426
M. S. Fofana United States 10 108 0.6× 50 0.4× 151 2.3× 57 0.9× 1 0.0× 28 259
A. Evkin Ukraine 13 43 0.2× 59 0.4× 123 1.8× 13 0.2× 2 0.0× 23 370

Countries citing papers authored by Daniel Bruder

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Daniel Bruder

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Bruder. A scholar is included among the top collaborators of Daniel Bruder 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 Daniel Bruder. Daniel Bruder 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.
Bruder, Daniel, et al.. (2024). A Koopman-based residual modeling approach for the control of a soft robot arm. The International Journal of Robotics Research. 44(3). 388–406. 5 indexed citations
2.
Dai, Tianxiang, et al.. (2024). Modeling and Experimental Validation of High‐Flow Fluid‐Driven Membrane Valves for Hyperactuated Soft Robots. SHILAP Revista de lepidopterología. 6(8). 1 indexed citations
3.
Remy, C. David, et al.. (2023). The “Fluid Jacobian”: Modeling force-motion relationships in fluid-driven soft robots. The International Journal of Robotics Research. 43(5). 628–645. 2 indexed citations
4.
Bruder, Daniel, Moritz A. Graule, Clark B. Teeple, & Robert J. Wood. (2023). Increasing the payload capacity of soft robot arms by localized stiffening. Science Robotics. 8(81). eadf9001–eadf9001. 31 indexed citations
5.
Bruder, Daniel, et al.. (2022). A Proprioceptive Method for Soft Robots Using Inertial Measurement Units. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 9379–9384. 5 indexed citations
6.
Bruder, Daniel & Robert J. Wood. (2021). The Chain-Link Actuator: Exploiting the Bending Stiffness of McKibben Artificial Muscles to Achieve Larger Contraction Ratios. IEEE Robotics and Automation Letters. 7(1). 542–548. 10 indexed citations
7.
Bruder, Daniel, et al.. (2020). Data-Driven Control of Soft Robots Using Koopman Operator Theory. IEEE Transactions on Robotics. 37(3). 948–961. 178 indexed citations breakdown →
8.
Bruder, Daniel, et al.. (2018). A Continuum Model for Fiber-Reinforced Soft Robot Actuators. Journal of Mechanisms and Robotics. 10(2). 36 indexed citations
9.
Bruder, Daniel, et al.. (2017). A Constitutive Model for Torsional Loads on Fluid-Driven Soft Robots. 5 indexed citations
10.
Bruder, Daniel, et al.. (2017). Model based control of fiber reinforced elastofluidic enclosures. 5539–5544. 9 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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