Francisco Cuéllar
- Social Psychology top 10%
- Cognitive Neuroscience
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Control and Systems Engineering
- Co-authors
- Gabriele TrovatoChristian PeñalozaSøren BechZheng‐Hua TanRui SongKlaus ZimmermannRichard BucknallFelix Becker
- Topics
- Social Robot Interaction and HRI (14 papers)Underwater Vehicles and Communication Systems (8 papers)Robotics and Automated Systems (6 papers)
- Journals
- SensorsIEEE Transactions on Automation Science and EngineeringInternational Journal of Social Robotics
- Partner nations
- PeruJapanUnited Kingdom
In The Last Decade
Francisco Cuéllar
47 papers receiving 348 citations
Peers
Comparison fields: 5 of 88
- Social Psychology 109
- Cognitive Neuroscience 65
- Computer Vision and Pattern Recognition 61
- Artificial Intelligence 56
- Control and Systems Engineering 55
Countries citing papers authored by Francisco Cuéllar
This map shows the geographic impact of Francisco Cuéllar'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 Francisco Cuéllar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francisco Cuéllar more than expected).
Fields of papers citing papers by Francisco Cuéllar
This network shows the impact of papers produced by Francisco Cuéllar. 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 Francisco Cuéllar. The network helps show where Francisco Cuéllar may publish in the future.
Co-authorship network of co-authors of Francisco Cuéllar
This figure shows the co-authorship network connecting the top 25 collaborators of Francisco Cuéllar. A scholar is included among the top collaborators of Francisco Cuéllar 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 Francisco Cuéllar. Francisco Cuéllar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 2 | |
| 9 | 1 | |
| 10 | 6 | |
| 11 | Adaptation Profiles in First-Time Robot Users: Towards Understanding Adaptation Patterns and Their Implications for Design | 5 |
| 12 | Design and implementation of an USV for large bodies of fresh waters at the highlands of Peru | 9 |
| 13 | 15 | |
| 14 | 10 | |
| 15 | 0 | |
| 16 | 6 | |
| 17 | 4 | |
| 18 | 12 | |
| 19 | 6 | |
| 20 | El Proyecto Gran Simio | 1 |
About Francisco Cuéllar
Francisco Cuéllar is a scholar working on Computer Science Applications, Human-Computer Interaction and Ocean Engineering, having authored 54 papers that have together received 363 indexed citations. Recurring topics across this work include Social Robot Interaction and HRI (14 papers), Underwater Vehicles and Communication Systems (8 papers) and Robotics and Automated Systems (6 papers). The work is most often cited by research in Human-Computer Interaction (50 citations), Social Psychology (109 citations) and Computer Science Applications (21 citations). Francisco Cuéllar has collaborated with scholars based in Peru, Japan and United Kingdom. Frequent co-authors include Gabriele Trovato, Christian Peñaloza, Søren Bech, Zheng‐Hua Tan, Rui Song, Klaus Zimmermann, Richard Bucknall, Felix Becker, Masaru Kojima and Yasushi Mae. Their work appears in journals such as Sensors, IEEE Transactions on Automation Science and Engineering and International Journal of Social Robotics.
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.