Benjamin Unger
- Numerical Analysis top 5%
- Numerical methods for differential equations 8
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- Model Reduction and Neural Networks 20
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- Probabilistic and Robust Engineering Design 5
- Control and Systems Engineering top 10%
- Control and Stability of Dynamical Systems 6
- Control Systems and Identification 4
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- Numerical methods in engineering 3
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- Neural Networks and Applications 2
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- Nuclear reactor physics and engineering 2
- Co-authors
- Philipp SchulzeVolker MehrmannSerkan GugercinJörg FehrChristopher BeattieTobias BreitenRobert AltmannStephan Trenn
- Journals
- SIAM Journal on Control and Optimization (2 papers)Advances in Computational Mathematics (2 papers)Electronic Journal of Linear Algebra (1 paper)
- Partner nations
- GermanyUnited StatesNetherlands
In The Last Decade
Benjamin Unger
22 papers receiving 268 citations
Peers
Comparison fields: 5 of 40
- Numerical Analysis 92
- Statistical and Nonlinear Physics 187
- Statistics, Probability and Uncertainty 47
- Control and Systems Engineering 130
- Computational Mathematics 2
Countries citing papers authored by Benjamin Unger
This map shows the geographic impact of Benjamin Unger'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 Unger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin Unger more than expected).
Fields of papers citing papers by Benjamin Unger
This network shows the impact of papers produced by Benjamin Unger. 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 Unger. The network helps show where Benjamin Unger may publish in the future.
Co-authorship network
The 12 scholars most cited alongside Benjamin Unger, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 3 | |
| 6 | 2023 | 44 | |
| 7 | 2023 | 10 | |
| 8 | 2022 | 40 | |
| 9 | 2022 | 9 | |
| 10 | 2022 | 2 | |
| 11 | 2022 | 15 | |
| 12 | 2021 | 2 | |
| 13 | 2021 | 8 | |
| 14 | 2021 | 3 | |
| 15 | 2019 | 22 | |
| 16 | 2019 | 4 | |
| 17 | 2018 | 1 | |
| 18 | 2018 | 9 | |
| 19 | 2017 | 37 | |
| 20 | 2016 | 28 |
About Benjamin Unger
Benjamin Unger is a scholar working on Statistical and Nonlinear Physics, Numerical Analysis, Structural Biology, Statistics, Probability and Uncertainty and Control and Systems Engineering, having authored 24 papers that have together received 280 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (20 papers), Numerical methods for differential equations (8 papers), Control and Stability of Dynamical Systems (6 papers), Probabilistic and Robust Engineering Design (5 papers), Control Systems and Identification (4 papers), Numerical methods in engineering (3 papers), Neural Networks and Applications (2 papers) and Nuclear reactor physics and engineering (2 papers). The work is most often cited by research in Numerical Analysis (92 citations), Statistical and Nonlinear Physics (187 citations), Statistics, Probability and Uncertainty (47 citations), Control and Systems Engineering (130 citations) and Computational Mathematics (2 citations). Benjamin Unger has collaborated with scholars based in Germany, United States and Netherlands. Frequent co-authors include Philipp Schulze, Volker Mehrmann, Serkan Gugercin, Jörg Fehr, Christopher Beattie, Tobias Breiten, Robert Altmann, Stephan Trenn, Bernard Haasdonk and Ion Victor Gosea. Their work appears in journals such as SIAM Journal on Control and Optimization, Advances in Computational Mathematics, Electronic Journal of Linear Algebra, IEEE Transactions on Neural Networks and Learning Systems and BIT Numerical Mathematics.
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.