Aditya Ganapathi
Impact in
- Control and Systems Engineering top 10%
- Robot Manipulation and Learning
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- Industrial Vision Systems and Defect Detection
- Manufacturing Process and Optimization
Papers in
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- Robot Manipulation and Learning 6
- Robotic Mechanisms and Dynamics 2
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- Soft Robotics and Applications 3
- Co-authors
- Ken Goldberg (7 shared papers)Ryan Hoque (6 shared papers)Ashwin Balakrishna (5 shared papers)Daniel Seita (5 shared papers)Nawid Jamali (5 shared papers)Katsu Yamane (5 shared papers)Soshi Iba (5 shared papers)Ajay Kumar Tanwani (3 shared papers)
- Journals
- Autonomous Robots (1 paper)2022 International Conference on Robotics and Automation (ICRA) (1 paper)2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (1 paper)
- Partner nations
- United States
In The Last Decade
Aditya Ganapathi
7 papers receiving 167 citations
Peers
Comparison fields: 5 of 28
- Control and Systems Engineering 116
- Industrial and Manufacturing Engineering 37
- Architecture 5
- Human-Computer Interaction 16
- Computer Vision and Pattern Recognition 52
Countries citing papers authored by Aditya Ganapathi
This map shows the geographic impact of Aditya Ganapathi'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 Aditya Ganapathi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aditya Ganapathi more than expected).
Fields of papers citing papers by Aditya Ganapathi
This network shows the impact of papers produced by Aditya Ganapathi. 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 Aditya Ganapathi. The network helps show where Aditya Ganapathi may publish in the future.
Co-authors
The 21 scholars most cited alongside Aditya Ganapathi, 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 | 2020 | 72 | |
| 2 | 2021 | 35 | |
| 3 | 2021 | 32 | |
| 4 | 2022 | 11 | |
| 5 | Learning to Smooth and Fold Real Fabric Using Dense Object Descriptors Trained on Synthetic Color Images | 2020 | 11 |
| 6 | Deep Imitation Learning of Sequential Fabric Smoothing Policies | 2019 | 9 |
| 7 | 2022 | 8 |
About Aditya Ganapathi
Aditya Ganapathi is a scholar working on Control and Systems Engineering, Biomedical Engineering, Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering and Computational Mechanics, having authored 7 papers that have together received 178 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (6 papers), Soft Robotics and Applications (3 papers), Optical measurement and interference techniques (2 papers), Robotic Mechanisms and Dynamics (2 papers), Manufacturing Process and Optimization (1 paper), Adversarial Robustness in Machine Learning (1 paper), Advanced Vision and Imaging (1 paper) and Modular Robots and Swarm Intelligence (1 paper). The work is most often cited by research in Control and Systems Engineering (116 citations), Industrial and Manufacturing Engineering (37 citations), Architecture (5 citations), Human-Computer Interaction (16 citations) and Computer Vision and Pattern Recognition (52 citations). Aditya Ganapathi has collaborated with scholars based in United States. Frequent co-authors include Ken Goldberg, Ryan Hoque, Ashwin Balakrishna, Daniel Seita, Nawid Jamali, Katsu Yamane, Soshi Iba, Ajay Kumar Tanwani, Minho Hwang and Brijen Thananjeyan. Their work appears in journals such as Autonomous Robots, 2022 International Conference on Robotics and Automation (ICRA) and 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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.