D. Ruspini

1.6k citations
12 papers · 952 · h-index 11

Impact in

Papers in

D. Ruspini

12 papers receiving 866 citations

Peers

D. Ruspini
Comparison fields: 5 of 55
  • Human-Computer Interaction 302
  • Control and Systems Engineering 465
  • Mechanical Engineering 617
  • Computer Vision and Pattern Recognition 327
  • Cognitive Neuroscience 246
Replace James J. Troy with:
James J. Troy United States
William A. McNeely United States
M.A. Srinivasan United States
K. Salisbury United States
Claude Andriot France
Thomas Massie United States
Dzmitry Tsetserukou Russia
Julius Kammerl Germany
W.S. Kim United States
Rui Fukui Japan
D. Ruspini relative to James J. Troy United States James J. Troy's profile →
Citations per field
00.5×3.3×
James J. Troy · 1×
Citations per year

Countries citing papers authored by D. Ruspini

Since Specialization
Citations

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

Fields of papers citing papers by D. Ruspini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside D. Ruspini, 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 D. Ruspini Line = papers co-authored together D. Ruspini links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 1997427
2 1996137
3 2002136
4 199659
5 200246
6 200238
7 200437
8 200134
9 200214
10 200213
11 200210
12
Beyond the Looking Glass : The Haptic Exploration of Virtual Environments
20031

About D. Ruspini

D. Ruspini is a scholar working on Control and Systems Engineering, Mechanical Engineering, Computer Vision and Pattern Recognition, Human-Computer Interaction and Cognitive Neuroscience, having authored 12 papers that have together received 952 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (10 papers), Teleoperation and Haptic Systems (8 papers), Robotic Path Planning Algorithms (6 papers), Modular Robots and Swarm Intelligence (3 papers), Virtual Reality Applications and Impacts (2 papers), Tactile and Sensory Interactions (2 papers), Robotic Mechanisms and Dynamics (1 paper) and Hand Gesture Recognition Systems (1 paper). The work is most often cited by research in Human-Computer Interaction (302 citations), Control and Systems Engineering (465 citations), Mechanical Engineering (617 citations), Computer Vision and Pattern Recognition (327 citations) and Cognitive Neuroscience (246 citations). D. Ruspini has collaborated with scholars based in United States. Frequent co-authors include Oussama Khatib, Krasimir Kolarov, Kyung Won Chang, A. Yáñez, Mats Holmberg, Kazuhito Yokoi, Luis Sentis, Oliver Brock and François Conti. Their work appears in journals such as The International Journal of Robotics Research, Communications of the ACM and Journal of Robotic Systems.

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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