Anke van Zuylen
- Statistical and Nonlinear Physics top 5%
- Computational Theory and Mathematics top 5%
- Artificial Intelligence
- Management Science and Operations Research top 10%
- Computer Networks and Communications top 10%
- Co-authors
- David P. WilliamsonChandrashekhar NagarajanTim CarnesStefan M. WildEdo LibertyMatthias PoloczekNir AilonGeorg Schnitger
- Topics
- Optimization and Search Problems (10 papers)Complexity and Algorithms in Graphs (10 papers)Game Theory and Voting Systems (6 papers)
- Cited by
- Statistical and Nonlinear PhysicsComputational Theory and MathematicsManagement Science and Operations Research
- Partner nations
- United StatesGermanyNetherlands
In The Last Decade
Anke van Zuylen
22 papers receiving 321 citations
Peers
Comparison fields: 5 of 42
- Statistical and Nonlinear Physics 156
- Computational Theory and Mathematics 111
- Artificial Intelligence 85
- Management Science and Operations Research 71
- Computer Networks and Communications 70
Countries citing papers authored by Anke van Zuylen
This map shows the geographic impact of Anke van Zuylen'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 Anke van Zuylen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anke van Zuylen more than expected).
Fields of papers citing papers by Anke van Zuylen
This network shows the impact of papers produced by Anke van Zuylen. 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 Anke van Zuylen. The network helps show where Anke van Zuylen may publish in the future.
Co-authorship network of co-authors of Anke van Zuylen
This figure shows the co-authorship network connecting the top 25 collaborators of Anke van Zuylen. A scholar is included among the top collaborators of Anke van Zuylen 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 Anke van Zuylen. Anke van Zuylen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 6 | |
| 3 | 3 | |
| 4 | 20 | |
| 5 | 5 | |
| 6 | 1 | |
| 7 | 7 | |
| 8 | 5 | |
| 9 | 4 | |
| 10 | 9 | |
| 11 | 5 | |
| 12 | 18 | |
| 13 | 1 | |
| 14 | 7 | |
| 15 | 42 | |
| 16 | 7 | |
| 17 | 17 | |
| 18 | 17 | |
| 19 | Deterministic Approximation Algorithms for Ranking and Clustering Problems | 5 |
| 20 | 1 |
About Anke van Zuylen
Anke van Zuylen is a scholar working on Industrial and Manufacturing Engineering, Computational Theory and Mathematics and Computer Networks and Communications, having authored 23 papers that have together received 341 indexed citations. Recurring topics across this work include Optimization and Search Problems (10 papers), Complexity and Algorithms in Graphs (10 papers) and Game Theory and Voting Systems (6 papers). The work is most often cited by research in Statistical and Nonlinear Physics (156 citations), Computational Theory and Mathematics (111 citations) and Management Science and Operations Research (71 citations). Anke van Zuylen has collaborated with scholars based in United States, Germany and Netherlands. Frequent co-authors include David P. Williamson, Chandrashekhar Nagarajan, Tim Carnes, Stefan M. Wild, Edo Liberty, Matthias Poloczek, Nir Ailon, Georg Schnitger, Kamal Jain and Suzanne van der Ster. Their work appears in journals such as Journal of the ACM, Mathematical Programming and SIAM Journal on Computing.
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.