Rylan Schaeffer
Impact in
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- Artificial Intelligence in Healthcare and Education
- Cognitive Neuroscience top 10%
- Neural dynamics and brain function
- Memory and Neural Mechanisms
Papers in
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- Memory and Neural Mechanisms 3
- Neural dynamics and brain function 2
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- Adversarial Robustness in Machine Learning 2
- Reinforcement Learning in Robotics 1
- Topic Modeling 1
- Co-authors
- Oluwasanmi Koyejo (4 shared papers)Brando Miranda (1 shared paper)Mikail Khona (2 shared papers)Ila Fiete (2 shared papers)Hengzhi Pei (1 shared paper)Chejian Xu (1 shared paper)Chulin Xie (1 shared paper)Mantas Mazeika (1 shared paper)
- Journals
- Nature (2 papers)Nature Methods (2 papers)neural information processing systems (6 papers)
- Partner nations
- United StatesUnited KingdomPortugal
In The Last Decade
Rylan Schaeffer
9 papers receiving 263 citations
Rylan Schaeffer's Hit Papers
Peers
Comparison fields: 5 of 61
- Health Informatics 13
- Cognitive Neuroscience 92
- Artificial Intelligence 88
- Safety Research 31
- Cellular and Molecular Neuroscience 18
Countries citing papers authored by Rylan Schaeffer
This map shows the geographic impact of Rylan Schaeffer'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 Rylan Schaeffer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rylan Schaeffer more than expected).
Fields of papers citing papers by Rylan Schaeffer
This network shows the impact of papers produced by Rylan Schaeffer. 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 Rylan Schaeffer. The network helps show where Rylan Schaeffer may publish in the future.
Co-authors
The 12 scholars most cited alongside Rylan Schaeffer, 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 | 2023 | 83 | |
| 2 | 2023 | 52 | |
| 3 | A brain-wide map of neural activity during complex behaviour Hit paper breakdown → | 2025 | 38 |
| 4 | 2024 | 33 | |
| 5 | 2022 | 27 | |
| 6 | Brain-wide representations of prior information in mouse decision-making Hit paper breakdown → | 2025 | 26 |
| 7 | 2023 | 6 | |
| 8 | 2023 | 5 | |
| 9 | 2024 | 3 | |
| 10 | 2025 | 0 |
About Rylan Schaeffer
Rylan Schaeffer is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Computer Vision and Pattern Recognition, Automotive Engineering and Safety Research, having authored 10 papers that have together received 273 indexed citations. Recurring topics across this work include Memory and Neural Mechanisms (3 papers), Adversarial Robustness in Machine Learning (2 papers), Neural dynamics and brain function (2 papers), Reinforcement Learning in Robotics (1 paper), Topic Modeling (1 paper), Human Pose and Action Recognition (1 paper), Multimodal Machine Learning Applications (1 paper) and Access Control and Trust (1 paper). The work is most often cited by research in Health Informatics (13 citations), Cognitive Neuroscience (92 citations), Artificial Intelligence (88 citations), Safety Research (31 citations) and Cellular and Molecular Neuroscience (18 citations). Rylan Schaeffer has collaborated with scholars based in United States, United Kingdom and Portugal. Frequent co-authors include Oluwasanmi Koyejo, Brando Miranda, Mikail Khona, Ila Fiete, Hengzhi Pei, Chejian Xu, Chulin Xie, Mantas Mazeika, Bo Li and Ethan Perez. Their work appears in journals such as Nature, Nature Methods 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.