Suna Bensch
- Artificial Intelligence top 10%
- Social Psychology
- Control and Systems Engineering
- Safety Research
- Cognitive Neuroscience
- Co-authors
- Thomas HellströmAleksandar JevtićStefan WermterMartin KutribHenning BordihnFrank DrewesBrink van der MerweHelmut Jürgensen
- Topics
- Natural Language Processing Techniques (8 papers)Social Robot Interaction and HRI (8 papers)Topic Modeling (6 papers)
In The Last Decade
Suna Bensch
23 papers receiving 158 citations
Peers
Comparison fields: 5 of 50
- Artificial Intelligence 105
- Social Psychology 76
- Control and Systems Engineering 32
- Safety Research 27
- Cognitive Neuroscience 21
Countries citing papers authored by Suna Bensch
This map shows the geographic impact of Suna Bensch'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 Suna Bensch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suna Bensch more than expected).
Fields of papers citing papers by Suna Bensch
This network shows the impact of papers produced by Suna Bensch. 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 Suna Bensch. The network helps show where Suna Bensch may publish in the future.
Co-authorship network of co-authors of Suna Bensch
This figure shows the co-authorship network connecting the top 25 collaborators of Suna Bensch. A scholar is included among the top collaborators of Suna Bensch 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 Suna Bensch. Suna Bensch is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 4 | |
| 5 | 18 | |
| 6 | Bias in machine learning - what is it good for? | 2 |
| 7 | Modelling Grice's Maxim of Quantity as Informativeness for Short Text | 1 |
| 8 | Towards Verbal Explanations by Collaborating Robot Teams | 1 |
| 9 | Natural Language Communication with Social Robots for Assisted Living | 1 |
| 10 | 0 | |
| 11 | Modeling Interaction for Understanding in HRI | 0 |
| 12 | Predicting User Competence from Linguistic Data | 2 |
| 13 | 18 | |
| 14 | Grammatical Inference of Graph Transformation Rules | 0 |
| 15 | Inferring Robot Actions from Verbal Commands Using Shallow Semantic Parsing | 1 |
| 16 | 3 | |
| 17 | Incremental Construction of Millstream Configurations Using Graph Transformation | 2 |
| 18 | Millstream Systems -- a Formal Model for Linking Language Modules by Interfaces | 3 |
| 19 | 7 | |
| 20 | Active Symbols in Pure Systems | 3 |
About Suna Bensch
Suna Bensch is a scholar working on Health Informatics, Artificial Intelligence and Software, having authored 29 papers that have together received 168 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (8 papers), Social Robot Interaction and HRI (8 papers) and Topic Modeling (6 papers). The work is most often cited by research in Social Psychology (76 citations), Artificial Intelligence (105 citations) and Safety Research (27 citations). Suna Bensch has collaborated with scholars based in Sweden, Germany and Spain. Frequent co-authors include Thomas Hellström, Aleksandar Jevtić, Stefan Wermter, Martin Kutrib, Henning Bordihn, Frank Drewes, Brink van der Merwe, Helmut Jürgensen, Markus Holzer and Avinash Kumar Singh. Their work appears in journals such as Applied Sciences, Theoretical Computer Science and Electronics.
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.