Hubert Eichner
Impact in
- Artificial Intelligence top 0.5%
- Privacy-Preserving Technologies in Data
- Cryptography and Data Security
- Stochastic Gradient Optimization Techniques
- Internet Traffic Analysis and Secure E-voting
- Adversarial Robustness in Machine Learning
- Health Informatics top 2%
Papers in
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- Neural dynamics and brain function 6
-
- Neurobiology and Insect Physiology Research 5
- Co-authors
- Alexander Borst (6 shared papers)Maximilian Joesch (2 shared papers)Dierk F. Reiff (1 shared paper)Bettina Schnell (1 shared paper)Franz Weber (2 shared papers)Michael L. Hines (1 shared paper)Hermann Cuntz (1 shared paper)Etienne Serbe-Kamp (1 shared paper)
- Journals
- PLoS ONE (2 papers)Neuron (1 paper)Journal of Computational Neuroscience (1 paper)New Journal of Physics (1 paper)PLoS Computational Biology (1 paper)
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Hubert Eichner
12 papers receiving 3.2k citations
Hubert Eichner's Hit Papers
Peers
Comparison fields: 5 of 115
- Artificial Intelligence 2.3k
- Health Informatics 82
- Computer Science Applications 250
- Computer Networks and Communications 490
- Information Systems 333
Countries citing papers authored by Hubert Eichner
This map shows the geographic impact of Hubert Eichner'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 Hubert Eichner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hubert Eichner more than expected).
Fields of papers citing papers by Hubert Eichner
This network shows the impact of papers produced by Hubert Eichner. 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 Hubert Eichner. The network helps show where Hubert Eichner may publish in the future.
Co-authors
The 14 scholars most cited alongside Hubert Eichner, 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 | Advances and Open Problems in Federated Learning Hit paper breakdown → | 2020 | 3000 |
| 2 | 2011 | 145 | |
| 3 | 2013 | 57 | |
| 4 | 2008 | 36 | |
| 5 | 2009 | 17 | |
| 6 | 2010 | 14 | |
| 7 | 2008 | 12 | |
| 8 | 2017 | 8 | |
| 9 | 2006 | 4 | |
| 10 | 2024 | 4 | |
| 11 | 2006 | 1 | |
| 12 | 2011 | 1 |
About Hubert Eichner
Hubert Eichner is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience, Hardware and Architecture, Artificial Intelligence and Ecology, Evolution, Behavior and Systematics, having authored 12 papers that have together received 3.3k indexed citations. Recurring topics across this work include Neural dynamics and brain function (6 papers), Neurobiology and Insect Physiology Research (5 papers), Neural Networks and Applications (3 papers), Insect and Arachnid Ecology and Behavior (2 papers), Cryptography and Data Security (2 papers), Parallel Computing and Optimization Techniques (2 papers), Privacy-Preserving Technologies in Data (2 papers) and Plant and animal studies (1 paper). The work is most often cited by research in Artificial Intelligence (2.3k citations), Health Informatics (82 citations), Computer Science Applications (250 citations), Computer Networks and Communications (490 citations) and Information Systems (333 citations). Hubert Eichner has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Alexander Borst, Maximilian Joesch, Dierk F. Reiff, Bettina Schnell, Franz Weber, Michael L. Hines, Hermann Cuntz, Etienne Serbe-Kamp, Aljoscha Leonhardt and Matthias Meier. Their work appears in journals such as PLoS ONE, Neuron, Journal of Computational Neuroscience, New Journal of Physics and PLoS Computational Biology.
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.