Benjamin Doerr
Impact in
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- Advanced Multi-Objective Optimization Algorithms
- Artificial Intelligence top 5%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Algorithms and Data Compression
- Reinforcement Learning in Robotics
Papers in
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- Evolutionary Algorithms and Applications 24
- Metaheuristic Optimization Algorithms Research 23
- Algorithms and Data Compression 5
- Artificial Intelligence in Games 3
- Reinforcement Learning in Robotics 3
- Machine Learning and Algorithms 2
- Bayesian Modeling and Causal Inference 2
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- Advanced Multi-Objective Optimization Algorithms 13
- Co-authors
- Carsten Witt (10 shared papers)Frank Neumann (3 shared papers)Mahmoud Fouz (2 shared papers)Zhongdi Qu (4 shared papers)Jing Yang (3 shared papers)Dirk Sudholt (3 shared papers)Denis Antipov (2 shared papers)Andrew M. Sutton (1 shared paper)
In The Last Decade
Benjamin Doerr
33 papers receiving 601 citations
Peers
Comparison fields: 5 of 63
- Computational Theory and Mathematics 342
- Artificial Intelligence 498
- Industrial and Manufacturing Engineering 54
- Computer Networks and Communications 76
- Management Science and Operations Research 39
Countries citing papers authored by Benjamin Doerr
This map shows the geographic impact of Benjamin Doerr'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 Benjamin Doerr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin Doerr more than expected).
Fields of papers citing papers by Benjamin Doerr
This network shows the impact of papers produced by Benjamin Doerr. 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 Benjamin Doerr. The network helps show where Benjamin Doerr may publish in the future.
Co-authors
The 17 scholars most cited alongside Benjamin Doerr, 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 34 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 112 | |
| 2 | 2007 | 44 | |
| 3 | 2011 | 43 | |
| 4 | 2010 | 38 | |
| 5 | 2018 | 35 | |
| 6 | 2017 | 35 | |
| 7 | 2023 | 29 | |
| 8 | 2010 | 27 | |
| 9 | 2019 | 22 | |
| 10 | 2016 | 21 | |
| 11 | 2019 | 20 | |
| 12 | 2013 | 20 | |
| 13 | 2018 | 20 | |
| 14 | 2022 | 17 | |
| 15 | 2019 | 17 | |
| 16 | 2017 | 16 | |
| 17 | 2022 | 12 | |
| 18 | Memory-Constrained Algorithms for Shortest Path Problem | 2011 | 10 |
| 19 | 2020 | 10 | |
| 20 | 2020 | 9 |
About Benjamin Doerr
Benjamin Doerr is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Molecular Biology, Signal Processing and Management Science and Operations Research, having authored 34 papers that have together received 608 indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (24 papers), Metaheuristic Optimization Algorithms Research (23 papers), Advanced Multi-Objective Optimization Algorithms (13 papers), Algorithms and Data Compression (5 papers), Artificial Intelligence in Games (3 papers), Reinforcement Learning in Robotics (3 papers), Machine Learning and Algorithms (2 papers) and Bayesian Modeling and Causal Inference (2 papers). The work is most often cited by research in Computational Theory and Mathematics (342 citations), Artificial Intelligence (498 citations), Industrial and Manufacturing Engineering (54 citations), Computer Networks and Communications (76 citations) and Management Science and Operations Research (39 citations). Benjamin Doerr has collaborated with scholars based in France, Germany and Denmark. Frequent co-authors include Carsten Witt, Frank Neumann, Mahmoud Fouz, Zhongdi Qu, Jing Yang, Dirk Sudholt, Denis Antipov, Andrew M. Sutton, Timo Kötzing and Martin S. Krejca. Their work appears in journals such as Algorithmica, Theoretical Computer Science, Artificial Intelligence, Soft Computing 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.