Benjamin Eysenbach
Impact in
-
- Data Visualization and Analytics
- Multimodal Machine Learning Applications
- Artificial Intelligence top 10%
- Reinforcement Learning in Robotics
- Explainable Artificial Intelligence (XAI)
- Advanced Clustering Algorithms Research
Papers in
-
- Reinforcement Learning in Robotics 8
- AI-based Problem Solving and Planning 2
- Domain Adaptation and Few-Shot Learning 1
- Machine Learning and Algorithms 1
- Adversarial Robustness in Machine Learning 1
- Algorithms and Data Compression 1
-
- Decision-Making and Behavioral Economics 1
- Co-authors
- Sergey Levine (9 shared papers)Adam Perer (1 shared paper)Walter F. Stewart (1 shared paper)Kenney Ng (1 shared paper)Bum Chul Kwon (1 shared paper)Christopher R. deFilippi (1 shared paper)Gregory Kahn (1 shared paper)Nicholas Rhinehart (1 shared paper)
- Journals
- IEEE Transactions on Visualization and Computer Graphics (1 paper)Proceedings - IEEE International Conference on Robotics and Automation/Proceedings (2 papers)neural information processing systems (9 papers)
- Partner nations
- United States
In The Last Decade
Benjamin Eysenbach
9 papers receiving 190 citations
Peers
Comparison fields: 5 of 41
- Computer Vision and Pattern Recognition 78
- Artificial Intelligence 88
- Aerospace Engineering 24
- Signal Processing 5
- Control and Systems Engineering 14
Countries citing papers authored by Benjamin Eysenbach
This map shows the geographic impact of Benjamin Eysenbach'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 Eysenbach with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin Eysenbach more than expected).
Fields of papers citing papers by Benjamin Eysenbach
This network shows the impact of papers produced by Benjamin Eysenbach. 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 Eysenbach. The network helps show where Benjamin Eysenbach may publish in the future.
Co-authors
The 24 scholars most cited alongside Benjamin Eysenbach, 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 | 105 | |
| 2 | 2021 | 54 | |
| 3 | 2022 | 20 | |
| 4 | 2022 | 3 | |
| 5 | 2022 | 3 | |
| 6 | 2022 | 2 | |
| 7 | 2022 | 2 | |
| 8 | 2023 | 1 | |
| 9 | 2023 | 1 | |
| 10 | 2024 | 0 | |
| 11 | 2025 | 0 | |
| 12 | 2025 | 0 |
About Benjamin Eysenbach
Benjamin Eysenbach is a scholar working on Artificial Intelligence, General Decision Sciences, Computational Theory and Mathematics, Strategy and Management and Computer Vision and Pattern Recognition, having authored 12 papers that have together received 191 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (8 papers), AI-based Problem Solving and Planning (2 papers), Data Visualization and Analytics (1 paper), Domain Adaptation and Few-Shot Learning (1 paper), Machine Learning and Algorithms (1 paper), Decision-Making and Behavioral Economics (1 paper), Adversarial Robustness in Machine Learning (1 paper) and Algorithms and Data Compression (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (78 citations), Artificial Intelligence (88 citations), Aerospace Engineering (24 citations), Signal Processing (5 citations) and Control and Systems Engineering (14 citations). Benjamin Eysenbach has collaborated with scholars based in United States. Frequent co-authors include Sergey Levine, Adam Perer, Walter F. Stewart, Kenney Ng, Bum Chul Kwon, Christopher R. deFilippi, Gregory Kahn, Nicholas Rhinehart, Dhruv Shah and Russ R. Salakhutdinov. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Proceedings - IEEE International Conference on Robotics and Automation/Proceedings and neural information processing systems.
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.