Doğan Çörüş
Impact in
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- Advanced Multi-Objective Optimization Algorithms
- Artificial Intelligence top 10%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
Papers in
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- Metaheuristic Optimization Algorithms Research 10
- Evolutionary Algorithms and Applications 6
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- Artificial Immune Systems Applications 5
- Co-authors
- Pietro S. Oliveto (10 shared papers)Per Kristian Lehre (4 shared papers)Duc-Cuong Dang (2 shared papers)Anton V. Eremeev (1 shared paper)D. Yazdani (4 shared papers)Dirk Sudholt (3 shared papers)Frank Neumann (2 shared papers)Jun He (2 shared papers)
- Journals
- IEEE Transactions on Evolutionary Computation (3 papers)Algorithmica (1 paper)Journal of Theoretical Biology (1 paper)Artificial Intelligence (1 paper)Evolutionary Computation (1 paper)
- Partner nations
- United KingdomTürkiyeChina
In The Last Decade
Doğan Çörüş
14 papers receiving 273 citations
Peers
Comparison fields: 5 of 49
- Computational Theory and Mathematics 113
- Artificial Intelligence 177
- Industrial and Manufacturing Engineering 27
- Software 4
- Management Science and Operations Research 12
Countries citing papers authored by Doğan Çörüş
This map shows the geographic impact of Doğan Çörüş'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 Doğan Çörüş with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Doğan Çörüş more than expected).
Fields of papers citing papers by Doğan Çörüş
This network shows the impact of papers produced by Doğan Çörüş. 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 Doğan Çörüş. The network helps show where Doğan Çörüş may publish in the future.
Co-authors
The 15 scholars most cited alongside Doğan Çörüş, 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 | 80 | |
| 2 | 2017 | 78 | |
| 3 | 2015 | 20 | |
| 4 | 2019 | 19 | |
| 5 | 2017 | 17 | |
| 6 | 2015 | 12 | |
| 7 | 2016 | 12 | |
| 8 | 2021 | 11 | |
| 9 | 2021 | 8 | |
| 10 | 2013 | 7 | |
| 11 | 2018 | 5 | |
| 12 | 2015 | 3 | |
| 13 | 2024 | 1 | |
| 14 | 2025 | 1 |
About Doğan Çörüş
Doğan Çörüş is a scholar working on Artificial Intelligence, Biomedical Engineering, Computational Theory and Mathematics, Immunology and Molecular Biology, having authored 14 papers that have together received 274 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (10 papers), Evolutionary Algorithms and Applications (6 papers), Artificial Immune Systems Applications (5 papers), T-cell and B-cell Immunology (4 papers), Advanced Multi-Objective Optimization Algorithms (4 papers), Immune Cell Function and Interaction (3 papers), Viral Infectious Diseases and Gene Expression in Insects (1 paper) and NF-κB Signaling Pathways (1 paper). The work is most often cited by research in Computational Theory and Mathematics (113 citations), Artificial Intelligence (177 citations), Industrial and Manufacturing Engineering (27 citations), Software (4 citations) and Management Science and Operations Research (12 citations). Doğan Çörüş has collaborated with scholars based in United Kingdom, Türkiye and China. Frequent co-authors include Pietro S. Oliveto, Per Kristian Lehre, Duc-Cuong Dang, Anton V. Eremeev, D. Yazdani, Dirk Sudholt, Frank Neumann, Jun He, Thomas Jansen and Christine Zarges. Their work appears in journals such as IEEE Transactions on Evolutionary Computation, Algorithmica, Journal of Theoretical Biology, Artificial Intelligence and Evolutionary Computation.
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.