Daniel Kappler

1.3k citations
20 papers · 555 indexed · h-index 12

Impact in

Papers in

Daniel Kappler

20 papers receiving 523 citations

Peers

Daniel Kappler
Comparison fields: 5 of 49
  • Control and Systems Engineering 393
  • Human-Computer Interaction 54
  • Computer Vision and Pattern Recognition 198
  • Artificial Intelligence 168
  • Biomedical Engineering 189
Replace Kai Huebner with:
Kai Huebner Sweden
Balakumar Sundaralingam United States
Vishal Satish United States
Yuzhe Qin United States
Douglas Morrison Australia
Ulrich Klank Germany
Zhixing Xue Germany
Minghao Gou China
Staffan Ekvall Sweden
Bowen Wen United States
Daniel Kappler relative to Kai Huebner Sweden Kai Huebner's profile →
Citations per field
00.5×10×15×19.3×
Kai Huebner · 1×
Citations per year

Countries citing papers authored by Daniel Kappler

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Kappler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 2015160
2 202382
3 201859
4 201536
5 201634
6 201131
7 201029
8 201625
9 201123
10 201622
11 201717
12 201611
13 20195
14 20154
15 20174
16 20114
17
Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards
20203
18 20183
19 20162
20 20161

About Daniel Kappler

Daniel Kappler is a scholar working on Business and International Management, Control and Systems Engineering, Human-Computer Interaction, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 20 papers that have together received 555 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (12 papers), Reinforcement Learning in Robotics (6 papers), Robotics and Sensor-Based Localization (3 papers), Innovation and Socioeconomic Development (2 papers), Hand Gesture Recognition Systems (2 papers), Human Pose and Action Recognition (2 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Robotic Mechanisms and Dynamics (2 papers). The work is most often cited by research in Control and Systems Engineering (393 citations), Human-Computer Interaction (54 citations), Computer Vision and Pattern Recognition (198 citations), Artificial Intelligence (168 citations) and Biomedical Engineering (189 citations). Daniel Kappler has collaborated with scholars based in Germany, United States and Spain. Frequent co-authors include Stefan Schaal, Jeannette Bohg, Manuel Wüthrich, Tamim Asfour, Stefan Schaal, Franziska Meier, Nathan Ratliff, Markus Przybylski, Brian Ichter and Fei Xia. Their work appears in journals such as Robotics and Autonomous Systems, IEEE Robotics and Automation Letters, The International Journal of Robotics Research, arXiv (Cornell University) and mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich).

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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