Priya Sundaresan

595 citations
11 papers · 201 indexed · h-index 9
Journals
IEEE Robotics and Automation Letters (1 paper)2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (1 paper)2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (1 paper)

In The Last Decade

Priya Sundaresan

11 papers receiving 189 citations

Peers

Priya Sundaresan
Comparison fields: 5 of 38
  • Control and Systems Engineering 126
  • Computer Vision and Pattern Recognition 58
  • Industrial and Manufacturing Engineering 26
  • Human-Computer Interaction 12
  • Computational Mechanics 31
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Viktor Makoviychuk United Kingdom
Theodoros Stouraitis Germany
Xuehe Zhang China
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Citations per field
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Citations per year

Countries citing papers authored by Priya Sundaresan

Since Specialization
Citations

This map shows the geographic impact of Priya Sundaresan'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 Priya Sundaresan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Priya Sundaresan more than expected).

Fields of papers citing papers by Priya Sundaresan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Priya Sundaresan. 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 Priya Sundaresan. The network helps show where Priya Sundaresan may publish in the future.

Co-authorship network

The 21 scholars most cited alongside Priya Sundaresan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Priya Sundaresan Line = papers co-authored together Priya Sundaresan links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 20251
2 20244
3 202310
4 202212
5 202220
6 202111
7 202135
8 202116
9 202067
10
Learning to Smooth and Fold Real Fabric Using Dense Object Descriptors Trained on Synthetic Color Images
202011
11 201914

About Priya Sundaresan

Priya Sundaresan is a scholar working on Control and Systems Engineering, Computer Graphics and Computer-Aided Design and Biomedical Engineering, having authored 11 papers that have together received 201 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (7 papers), Soft Robotics and Applications (5 papers), Robotic Mechanisms and Dynamics (2 papers), Robotics and Sensor-Based Localization (2 papers), Social Robot Interaction and HRI (1 paper), Surgical Simulation and Training (1 paper), Anatomy and Medical Technology (1 paper) and Human Motion and Animation (1 paper). The work is most often cited by research in Control and Systems Engineering (126 citations), Computer Vision and Pattern Recognition (58 citations) and Industrial and Manufacturing Engineering (26 citations). Priya Sundaresan has collaborated with scholars based in United States, Switzerland and Australia. Frequent co-authors include Brijen Thananjeyan, Ken Goldberg, Ashwin Balakrishna, Joseph E. Gonzalez, Michael Laskey, Jeannette Bohg, Rika Antonova, Kevin Stone, Minho Hwang and Daniel Seita. Their work appears in journals such as IEEE Robotics and Automation Letters, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 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.

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