Emanuele Ruffaldi

134 papers receiving 2.2k citations

Peers

Emanuele Ruffaldi
Comparison fields: 5 of 134
  • Human-Computer Interaction 526
  • Computer Science Applications 151
  • Cognitive Neuroscience 407
  • Rehabilitation 127
  • Developmental and Educational Psychology 250
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Gentiane Venture Japan
Mohamad Eid United Arab Emirates
Jani Mäntyjärvi Finland
Kristof Van Laerhoven Germany
Wenbing Zhao United States
Emanuele Menegatti Italy
Cem Ersoy Türkiye
Burkhard C. Wünsche New Zealand
Zhe Cao China
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Citations per year

Countries citing papers authored by Emanuele Ruffaldi

Since Specialization
Citations

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

Fields of papers citing papers by Emanuele Ruffaldi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Emanuele Ruffaldi, 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 Emanuele Ruffaldi Line = papers co-authored together Emanuele Ruffaldi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 138 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017286
2 2015204
3 2018148
4 2015110
5 201775
6 201564
7 200953
8 201742
9 201341
10 201341
11 201140
12 201738
13 201736
14 200633
15 200632
16 200631
17 202029
18 201928
19 202027
20 200927

About Emanuele Ruffaldi

Emanuele Ruffaldi is a scholar working on Mechanical Engineering, Human-Computer Interaction, Cognitive Neuroscience, Computer Vision and Pattern Recognition and Control and Systems Engineering, having authored 138 papers that have together received 2.3k indexed citations. Recurring topics across this work include Teleoperation and Haptic Systems (41 papers), Virtual Reality Applications and Impacts (31 papers), Tactile and Sensory Interactions (26 papers), Robot Manipulation and Learning (15 papers), Numerical Methods and Algorithms (10 papers), Human Motion and Animation (9 papers), Motor Control and Adaptation (9 papers) and Sport Psychology and Performance (8 papers). The work is most often cited by research in Human-Computer Interaction (526 citations), Computer Science Applications (151 citations), Cognitive Neuroscience (407 citations), Rehabilitation (127 citations) and Developmental and Educational Psychology (250 citations). Emanuele Ruffaldi has collaborated with scholars based in Italy, United States and France. Frequent co-authors include Carlo Alberto Avizzano, Alessandro Filippeschi, Lorenzo Peppoloni, Massimo Bergamasco, Giacomo Dabisias, Daniel Spikol, Mutlu Cukurova, Paolo Tripicchio, Massimo Satler and Didier Stricker. Their work appears in journals such as PRESENCE Virtual and Augmented Reality, Advanced Robotics, Robotics and Autonomous Systems, The Visual Computer and Sensors.

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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