Karinne Ramírez-Amaro

35 papers receiving 615 citations

Peers

Karinne Ramírez-Amaro
Comparison fields: 5 of 60
  • Control and Systems Engineering 332
  • Human-Computer Interaction 71
  • Computer Vision and Pattern Recognition 263
  • Artificial Intelligence 196
  • Industrial and Manufacturing Engineering 58
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Jim Mainprice United States
Matteo Saveriano Italy
Rudolf Lioutikov Germany
Alexis Maldonado Germany
Marco Ewerton Germany
Alexandros Paraschos Germany
Albert Causo Singapore
Junpei Zhong United Kingdom
João Silvério Italy
Frank Wallhoff Germany
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Citations per field
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Citations per year

Countries citing papers authored by Karinne Ramírez-Amaro

Since Specialization
Citations

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

Fields of papers citing papers by Karinne Ramírez-Amaro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Karinne Ramírez-Amaro. 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 Karinne Ramírez-Amaro. The network helps show where Karinne Ramírez-Amaro may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201590
2 201159
3 201741
4 201740
5 201536
6 201735
7 201425
8 201623
9 202122
10 201522
11 201922
12 201517
13 201917
14 202216
15 201316
16 201415
17 201615
18 201414
19 201913
20 201712

About Karinne Ramírez-Amaro

Karinne Ramírez-Amaro is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Social Psychology and Biomedical Engineering, having authored 37 papers that have together received 627 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (13 papers), Human Pose and Action Recognition (13 papers), AI-based Problem Solving and Planning (7 papers), Multimodal Machine Learning Applications (6 papers), Social Robot Interaction and HRI (6 papers), Time Series Analysis and Forecasting (4 papers), Natural Language Processing Techniques (3 papers) and Context-Aware Activity Recognition Systems (3 papers). The work is most often cited by research in Control and Systems Engineering (332 citations), Human-Computer Interaction (71 citations), Computer Vision and Pattern Recognition (263 citations), Artificial Intelligence (196 citations) and Industrial and Manufacturing Engineering (58 citations). Karinne Ramírez-Amaro has collaborated with scholars based in Germany, Sweden and Japan. Frequent co-authors include Gordon Cheng, Michael Beetz, Emmanuel Dean‐Leon, Florian Bergner, Tetsunari Inamura, Agnieszka Wykowska, David Weikersdorfer, Sebastian Albrecht, Marion Leibold and Michael Ulbrich. Their work appears in journals such as Robotics and Autonomous Systems, IEEE Robotics and Automation Letters, ACM Transactions on Interactive Intelligent Systems, Interaction Studies Social Behaviour and Communication in Biological and Artificial Systems and Advanced 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.

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