Kai Kunze
- Human-Computer Interaction top 0.1%
- Gaze Tracking and Assistive Technology 62
- Interactive and Immersive Displays 44
- Virtual Reality Applications and Impacts 30
- Innovative Human-Technology Interaction 17
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- Context-Aware Activity Recognition Systems 28
- Augmented Reality Applications 19
- Cognitive Neuroscience top 2%
- Tactile and Sensory Interactions 52
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- Emotion and Mood Recognition 14
- Co-authors
- Paul LukowiczKoichi KiseMasahiko İnamiYun Suen PaiTilman DinglerGeorge ChernyshovShoya IshimaruBenjamin Tag
- Journals
- IEEE Pervasive Computing (5 papers)ACM Transactions on Computer-Human Interaction (3 papers)Virtual Reality (2 papers)
- Partner nations
- JapanGermanyUnited Kingdom
In The Last Decade
Kai Kunze
192 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 125
- Human-Computer Interaction 1.3k
- Computer Vision and Pattern Recognition 940
- Cognitive Neuroscience 778
- Experimental and Cognitive Psychology 214
- Computer Science Applications 78
Countries citing papers authored by Kai Kunze
This map shows the geographic impact of Kai Kunze'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 Kai Kunze with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai Kunze more than expected).
Fields of papers citing papers by Kai Kunze
This network shows the impact of papers produced by Kai Kunze. 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 Kai Kunze. The network helps show where Kai Kunze may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kai Kunze, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 0 | |
| 7 | 2023 | 16 | |
| 8 | 2023 | 6 | |
| 9 | 2023 | 2 | |
| 10 | 2022 | 1 | |
| 11 | 2022 | 14 | |
| 12 | 2022 | 1 | |
| 13 | 2016 | 10 | |
| 14 | 2016 | 11 | |
| 15 | 2016 | 9 | |
| 16 | 2016 | 12 | |
| 17 | 2015 | 0 | |
| 18 | Towards dynamically configurable context recognition systems | 2012 | 1 |
| 19 | 2007 | 29 | |
| 20 | LifeNet: an Ad-hoc Sensor Network and Wearable System to Provide Firefighters with Navigation Support | 2007 | 23 |
About Kai Kunze
Kai Kunze is a scholar working on Human-Computer Interaction, Cognitive Neuroscience and Computer Vision and Pattern Recognition, having authored 203 papers that have together received 2.6k indexed citations. Recurring topics across this work include Gaze Tracking and Assistive Technology (62 papers), Tactile and Sensory Interactions (52 papers), Interactive and Immersive Displays (44 papers), Virtual Reality Applications and Impacts (30 papers), Context-Aware Activity Recognition Systems (28 papers), Augmented Reality Applications (19 papers), Innovative Human-Technology Interaction (17 papers) and Emotion and Mood Recognition (14 papers). The work is most often cited by research in Human-Computer Interaction (1.3k citations), Computer Vision and Pattern Recognition (940 citations) and Cognitive Neuroscience (778 citations). Kai Kunze has collaborated with scholars based in Japan, Germany and United Kingdom. Frequent co-authors include Paul Lukowicz, Koichi Kise, Masahiko İnami, Yun Suen Pai, Tilman Dingler, George Chernyshov, Shoya Ishimaru, Benjamin Tag, Kouta Minamizawa and Katsutoshi Masai. Their work appears in journals such as IEEE Pervasive Computing, ACM Transactions on Computer-Human Interaction, Virtual Reality, Computer and IEEE Multimedia.
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.