Chris Schwiegelshohn
Impact in
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- Complexity and Algorithms in Graphs
- Artificial Intelligence top 10%
- Advanced Clustering Algorithms Research
- Privacy-Preserving Technologies in Data
- Data Stream Mining Techniques
Papers in
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- Privacy-Preserving Technologies in Data 5
- Machine Learning and Algorithms 4
- Advanced Clustering Algorithms Research 3
- Algorithms and Data Compression 3
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- Optimization and Search Problems 9
- Co-authors
- Christian Sohler (4 shared papers)Melanie Schmidt (2 shared papers)Fabrizio Grandoni (4 shared papers)Shay Solomon (3 shared papers)Vincent Cohen-Addad (5 shared papers)Luca Becchetti (1 shared paper)Aris Anagnostopoulos (1 shared paper)Uwe Schwiegelshohn (2 shared papers)
In The Last Decade
Chris Schwiegelshohn
25 papers receiving 203 citations
Peers
Comparison fields: 5 of 38
- Computational Theory and Mathematics 71
- Artificial Intelligence 137
- Signal Processing 36
- Computer Graphics and Computer-Aided Design 11
- Computer Networks and Communications 68
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 25 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
Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 34 | |
| 2 | 2020 | 31 | |
| 3 | 2015 | 21 | |
| 4 | 2017 | 20 | |
| 5 | 2020 | 14 | |
| 6 | 2022 | 11 | |
| 7 | 2016 | 10 | |
| 8 | 2022 | 9 | |
| 9 | 2023 | 8 | |
| 10 | 2019 | 8 | |
| 11 | 2019 | 5 | |
| 12 | 2019 | 5 | |
| 13 | 2022 | 5 | |
| 14 | 2019 | 4 | |
| 15 | 2009 | 4 | |
| 16 | 2016 | 4 | |
| 17 | 2018 | 3 | |
| 18 | 2018 | 3 | |
| 19 | 2012 | 3 | |
| 20 | 2020 | 3 |
About Chris Schwiegelshohn
Chris Schwiegelshohn is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computational Theory and Mathematics, Computer Vision and Pattern Recognition and Industrial and Manufacturing Engineering, having authored 29 papers that have together received 214 indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (10 papers), Optimization and Search Problems (9 papers), Face and Expression Recognition (5 papers), Privacy-Preserving Technologies in Data (5 papers), Machine Learning and Algorithms (4 papers), Advanced Clustering Algorithms Research (3 papers), Facility Location and Emergency Management (3 papers) and Algorithms and Data Compression (3 papers). The work is most often cited by research in Computational Theory and Mathematics (71 citations), Artificial Intelligence (137 citations), Signal Processing (36 citations), Computer Graphics and Computer-Aided Design (11 citations) and Computer Networks and Communications (68 citations). Chris Schwiegelshohn has collaborated with scholars based in Denmark, Germany and Italy. Frequent co-authors include Christian Sohler, Melanie Schmidt, Fabrizio Grandoni, Shay Solomon, Vincent Cohen-Addad, Luca Becchetti, Aris Anagnostopoulos, Uwe Schwiegelshohn, Stefano Leonardi and Piotr Sankowski. Their work appears in journals such as Algorithmica, IEEE Transactions on Knowledge and Data Engineering, Operations Research Letters, Lecture notes in computer science and KI - Künstliche Intelligenz.
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.