Michael Kamp
Impact in
- Artificial Intelligence top 10%
- Privacy-Preserving Technologies in Data
- Explainable Artificial Intelligence (XAI)
- Stochastic Gradient Optimization Techniques
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- Advanced Database Systems and Queries
- IoT and Edge/Fog Computing
Papers in
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- Privacy-Preserving Technologies in Data 8
- Stochastic Gradient Optimization Techniques 6
- Data Stream Mining Techniques 3
- Explainable Artificial Intelligence (XAI) 3
- Domain Adaptation and Few-Shot Learning 2
- Machine Learning and Algorithms 2
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- Data Visualization and Analytics 4
- Co-authors
- Michael Möck (3 shared papers)Antonios Deligiannakis (1 shared paper)Nikos Giatrakos (1 shared paper)Minos Garofalakis (1 shared paper)Stefan Wrobel (5 shared papers)Peter Schlicht (2 shared papers)Fabian Hüger (2 shared papers)Mario Boley (8 shared papers)
- Journals
- IEEE Transactions on Visualization and Computer Graphics (2 papers)Journal of Systems and Software (1 paper)IEEE Computer Graphics and Applications (1 paper)Computer Methods and Programs in Biomedicine (1 paper)Lecture notes in computer science (5 papers)
- Partner nations
- GermanyAustraliaUnited Kingdom
In The Last Decade
Michael Kamp
29 papers receiving 346 citations
Peers
Comparison fields: 5 of 62
- Artificial Intelligence 157
- Computer Networks and Communications 89
- Health Informatics 6
- Computer Vision and Pattern Recognition 41
- Information Systems 34
Countries citing papers authored by Michael Kamp
This map shows the geographic impact of Michael Kamp'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 Michael Kamp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Kamp more than expected).
Fields of papers citing papers by Michael Kamp
This network shows the impact of papers produced by Michael Kamp. 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 Michael Kamp. The network helps show where Michael Kamp may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Kamp, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 90 | |
| 2 | 2019 | 75 | |
| 3 | 2022 | 26 | |
| 4 | 2024 | 26 | |
| 5 | 2021 | 23 | |
| 6 | 2014 | 20 | |
| 7 | 2020 | 15 | |
| 8 | 2021 | 12 | |
| 9 | 2013 | 10 | |
| 10 | 2016 | 8 | |
| 11 | 2019 | 7 | |
| 12 | 2021 | 4 | |
| 13 | 2025 | 4 | |
| 14 | 2014 | 3 | |
| 15 | 2016 | 3 | |
| 16 | 2020 | 3 | |
| 17 | 2020 | 3 | |
| 18 | 2020 | 3 | |
| 19 | 2023 | 3 | |
| 20 | 2025 | 3 |
About Michael Kamp
Michael Kamp is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Management Science and Operations Research and Computer Graphics and Computer-Aided Design, having authored 32 papers that have together received 353 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (8 papers), Stochastic Gradient Optimization Techniques (6 papers), Data Visualization and Analytics (4 papers), Data Stream Mining Techniques (3 papers), Explainable Artificial Intelligence (XAI) (3 papers), Domain Adaptation and Few-Shot Learning (2 papers), Data Mining Algorithms and Applications (2 papers) and Machine Learning and Algorithms (2 papers). The work is most often cited by research in Artificial Intelligence (157 citations), Computer Networks and Communications (89 citations), Health Informatics (6 citations), Computer Vision and Pattern Recognition (41 citations) and Information Systems (34 citations). Michael Kamp has collaborated with scholars based in Germany, Australia and United Kingdom. Frequent co-authors include Michael Möck, Antonios Deligiannakis, Nikos Giatrakos, Minos Garofalakis, Stefan Wrobel, Peter Schlicht, Fabian Hüger, Mario Boley, Izchak Sharfman and Daniel Keren. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Journal of Systems and Software, IEEE Computer Graphics and Applications, Computer Methods and Programs in Biomedicine and Lecture notes in computer science.
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.