Chris Schwiegelshohn
Impact in
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- Advanced Clustering Algorithms Research
- Advanced Graph Neural Networks
- Machine Learning and Algorithms
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- Face and Expression Recognition
Papers in
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- Privacy-Preserving Technologies in Data 3
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- Face and Expression Recognition 5
- Co-authors
- Vincent Cohen-Addad (5 shared papers)Christian Sohler (2 shared papers)Uwe Schwiegelshohn (2 shared papers)Aris Anagnostopoulos (1 shared paper)Luca Becchetti (1 shared paper)Robert Krauthgamer (1 shared paper)Stefano Leonardi (2 shared papers)David P. Woodruff (1 shared paper)
- Journals
- Operations Research Letters (1 paper)Algorithmica (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)KI - Künstliche Intelligenz (1 paper)SPIRE - Sciences Po Institutional REpository (1 paper)
In The Last Decade
Chris Schwiegelshohn
17 papers receiving 74 citations
Peers
Comparison fields: 5 of 26
- Artificial Intelligence 49
- Computer Vision and Pattern Recognition 25
- Signal Processing 13
- Computational Theory and Mathematics 17
- Computer Networks and Communications 20
Countries citing papers authored by Chris Schwiegelshohn
This map shows the geographic impact of Chris Schwiegelshohn'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 Chris Schwiegelshohn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris Schwiegelshohn more than expected).
Fields of papers citing papers by Chris Schwiegelshohn
This network shows the impact of papers produced by Chris Schwiegelshohn. 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 Chris Schwiegelshohn. The network helps show where Chris Schwiegelshohn may publish in the future.
Co-authors
The 24 scholars most cited alongside Chris Schwiegelshohn, 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 | 2017 | 18 | |
| 2 | 2020 | 12 | |
| 3 | 2019 | 8 | |
| 4 | 2022 | 7 | |
| 5 | 2016 | 6 | |
| 6 | 2019 | 4 | |
| 7 | 2016 | 3 | |
| 8 | 2009 | 3 | |
| 9 | 2022 | 3 | |
| 10 | 2020 | 3 | |
| 11 | 2019 | 2 | |
| 12 | 2018 | 2 | |
| 13 | 2018 | 2 | |
| 14 | 2024 | 1 | |
| 15 | 2024 | 1 | |
| 16 | 2021 | 1 | |
| 17 | 2017 | 1 | |
| 18 | 2024 | 0 | |
| 19 | 2023 | 0 |
About Chris Schwiegelshohn
Chris Schwiegelshohn is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Computational Theory and Mathematics and Industrial and Manufacturing Engineering, having authored 19 papers that have together received 77 indexed citations. Recurring topics across this work include Face and Expression Recognition (5 papers), Optimization and Search Problems (4 papers), Complexity and Algorithms in Graphs (4 papers), Caching and Content Delivery (3 papers), Scheduling and Optimization Algorithms (3 papers), Privacy-Preserving Technologies in Data (3 papers), Auction Theory and Applications (2 papers) and Ethics and Social Impacts of AI (2 papers). The work is most often cited by research in Artificial Intelligence (49 citations), Computer Vision and Pattern Recognition (25 citations), Signal Processing (13 citations), Computational Theory and Mathematics (17 citations) and Computer Networks and Communications (20 citations). Chris Schwiegelshohn has collaborated with scholars based in Italy, Denmark and Germany. Frequent co-authors include Vincent Cohen-Addad, Christian Sohler, Uwe Schwiegelshohn, Aris Anagnostopoulos, Luca Becchetti, Robert Krauthgamer, Stefano Leonardi, David P. Woodruff, Vladimir Braverman and Shay Solomon. Their work appears in journals such as Operations Research Letters, Algorithmica, IEEE Transactions on Knowledge and Data Engineering, KI - Künstliche Intelligenz and SPIRE - Sciences Po Institutional REpository.
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.