Matthew Chignoli
Impact in
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- Robotic Locomotion and Control
- Prosthetics and Rehabilitation Robotics
- Control and Systems Engineering top 10%
- Control and Dynamics of Mobile Robots
- Robot Manipulation and Learning
- Robotic Mechanisms and Dynamics
- Real-time simulation and control systems
Papers in
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- Robotic Locomotion and Control 8
- Prosthetics and Rehabilitation Robotics 5
- Soft Robotics and Applications 1
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- Robotic Mechanisms and Dynamics 3
- Co-authors
- Sangbae Kim (9 shared papers)Donghyun Kim (2 shared papers)Patrick M. Wensing (2 shared papers)Yanran Ding (2 shared papers)Gerardo Bledt (1 shared paper)Seungwoo Hong (1 shared paper)Jean-Jacques Slotine (1 shared paper)
- Journals
- IEEE Robotics and Automation Letters (1 paper)IEEE Access (1 paper)DSpace@MIT (Massachusetts Institute of Technology) (1 paper)2022 International Conference on Robotics and Automation (ICRA) (1 paper)
- Partner nations
- United States
In The Last Decade
Matthew Chignoli
8 papers receiving 275 citations
Peers
Comparison fields: 5 of 37
- Biomedical Engineering 224
- Control and Systems Engineering 119
- Computer Vision and Pattern Recognition 55
- Aerospace Engineering 37
- Mechanical Engineering 51
Countries citing papers authored by Matthew Chignoli
This map shows the geographic impact of Matthew Chignoli'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 Matthew Chignoli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Chignoli more than expected).
Fields of papers citing papers by Matthew Chignoli
This network shows the impact of papers produced by Matthew Chignoli. 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 Matthew Chignoli. The network helps show where Matthew Chignoli may publish in the future.
Co-authors
The 7 scholars most cited alongside Matthew Chignoli, 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 | 2021 | 99 | |
| 2 | 2020 | 58 | |
| 3 | 2020 | 34 | |
| 4 | 2021 | 31 | |
| 5 | 2022 | 20 | |
| 6 | 2024 | 18 | |
| 7 | 2022 | 18 | |
| 8 | 2023 | 11 | |
| 9 | 2024 | 0 | |
| 10 | 2024 | 0 |
About Matthew Chignoli
Matthew Chignoli is a scholar working on Biomedical Engineering, Control and Systems Engineering, Computer Vision and Pattern Recognition, Molecular Biology and Ecology, Evolution, Behavior and Systematics, having authored 10 papers that have together received 289 indexed citations. Recurring topics across this work include Robotic Locomotion and Control (8 papers), Prosthetics and Rehabilitation Robotics (5 papers), Robotic Mechanisms and Dynamics (3 papers), Robotic Path Planning Algorithms (3 papers), Aerospace Engineering and Energy Systems (1 paper), Bat Biology and Ecology Studies (1 paper), Soft Robotics and Applications (1 paper) and Muscle Physiology and Disorders (1 paper). The work is most often cited by research in Biomedical Engineering (224 citations), Control and Systems Engineering (119 citations), Computer Vision and Pattern Recognition (55 citations), Aerospace Engineering (37 citations) and Mechanical Engineering (51 citations). Matthew Chignoli has collaborated with scholars based in United States. Frequent co-authors include Sangbae Kim, Donghyun Kim, Patrick M. Wensing, Yanran Ding, Gerardo Bledt, Seungwoo Hong and Jean-Jacques Slotine. Their work appears in journals such as IEEE Robotics and Automation Letters, IEEE Access, DSpace@MIT (Massachusetts Institute of Technology) and 2022 International Conference on Robotics and Automation (ICRA).
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.