Nawid Jamali
- Cognitive Neuroscience top 5%
- Biomedical Engineering top 10%
- Control and Systems Engineering top 5%
- Computer Vision and Pattern Recognition top 10%
- Human-Computer Interaction top 5%
- Co-authors
- Claude SammutSoshi IbaLorenzo NataleDaniel SeitaKen GoldbergAshwin BalakrishnaRyan HoqueKatsu Yamane
- Topics
- Robot Manipulation and Learning (17 papers)Tactile and Sensory Interactions (9 papers)Advanced Sensor and Energy Harvesting Materials (6 papers)
- Partner nations
- United StatesItalyAustralia
In The Last Decade
Nawid Jamali
25 papers receiving 582 citations
Peers
Comparison fields: 5 of 52
- Cognitive Neuroscience 298
- Biomedical Engineering 291
- Control and Systems Engineering 266
- Computer Vision and Pattern Recognition 88
- Human-Computer Interaction 77
Countries citing papers authored by Nawid Jamali
This map shows the geographic impact of Nawid Jamali'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 Nawid Jamali with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nawid Jamali more than expected).
Fields of papers citing papers by Nawid Jamali
This network shows the impact of papers produced by Nawid Jamali. 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 Nawid Jamali. The network helps show where Nawid Jamali may publish in the future.
Co-authorship network of co-authors of Nawid Jamali
This figure shows the co-authorship network connecting the top 25 collaborators of Nawid Jamali. A scholar is included among the top collaborators of Nawid Jamali 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 Nawid Jamali. Nawid Jamali is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 8 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 38 | |
| 9 | 35 | |
| 10 | 72 | |
| 11 | 5 | |
| 12 | Robot Bed-Making: Deep Transfer Learning Using Depth Sensing of Deformable Fabric. | 10 |
| 13 | 31 | |
| 14 | 6 | |
| 15 | 39 | |
| 16 | 9 | |
| 17 | 2 | |
| 18 | 21 | |
| 19 | 167 | |
| 20 | 62 |
About Nawid Jamali
Nawid Jamali is a scholar working on Control and Systems Engineering, Cognitive Neuroscience and Human-Computer Interaction, having authored 26 papers that have together received 598 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (17 papers), Tactile and Sensory Interactions (9 papers) and Advanced Sensor and Energy Harvesting Materials (6 papers). The work is most often cited by research in Cognitive Neuroscience (298 citations), Human-Computer Interaction (77 citations) and Control and Systems Engineering (266 citations). Nawid Jamali has collaborated with scholars based in United States, Italy and Australia. Frequent co-authors include Claude Sammut, Soshi Iba, Lorenzo Natale, Daniel Seita, Ken Goldberg, Ashwin Balakrishna, Ryan Hoque, Katsu Yamane, Ajay Kumar Tanwani and Lorenzo Rosasco. Their work appears in journals such as IEEE Transactions on Robotics, Autonomous Robots and IEEE Robotics and Automation Letters.
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.