John Aslanides
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 10%
- Topic Modeling
- Adversarial Robustness in Machine Learning
- Natural Language Processing Techniques
- Explainable Artificial Intelligence (XAI)
- Reinforcement Learning in Robotics
- Privacy-Preserving Technologies in Data
Papers in
-
- Reinforcement Learning in Robotics 3
- Natural Language Processing Techniques 1
- Adversarial Robustness in Machine Learning 1
- Topic Modeling 1
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- Auction Theory and Applications 1
- Advanced Bandit Algorithms Research 1
- Co-authors
- Trevor Cai (1 shared paper)Ethan Perez (1 shared paper)Francis Song (1 shared paper)Geoffrey Irving (1 shared paper)Amelia Glaese (1 shared paper)Roman Ring (1 shared paper)Saffron Huang (1 shared paper)Albin Cassirer (1 shared paper)
- Journals
- Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)Adaptive Agents and Multi-Agents Systems (1 paper)Neural Information Processing Systems (2 papers)
- Partner nations
- United StatesUnited KingdomAustralia
In The Last Decade
John Aslanides
4 papers receiving 191 citations
John Aslanides's Hit Papers
Peers
Comparison fields: 5 of 51
- Health Informatics 19
- Artificial Intelligence 154
- Safety Research 29
- Computer Vision and Pattern Recognition 25
- Signal Processing 13
Countries citing papers authored by John Aslanides
This map shows the geographic impact of John Aslanides'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 John Aslanides with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Aslanides more than expected).
Fields of papers citing papers by John Aslanides
This network shows the impact of papers produced by John Aslanides. 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 John Aslanides. The network helps show where John Aslanides may publish in the future.
Co-authors
The 17 scholars most cited alongside John Aslanides, 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 | Red Teaming Language Models with Language Models Hit paper breakdown → | 2022 | 152 |
| 2 | Randomized prior functions for deep reinforcement learning | 2018 | 27 |
| 3 | 2020 | 21 | |
| 4 | When to use parametric models in reinforcement learning | 2019 | 8 |
| 5 | 2017 | 0 |
About John Aslanides
John Aslanides is a scholar working on Artificial Intelligence, Management Science and Operations Research, Economics and Econometrics, Safety Research and Infectious Diseases, having authored 5 papers that have together received 208 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (3 papers), Auction Theory and Applications (1 paper), Economic theories and models (1 paper), Natural Language Processing Techniques (1 paper), Adversarial Robustness in Machine Learning (1 paper), Sports Analytics and Performance (1 paper), Advanced Bandit Algorithms Research (1 paper) and Topic Modeling (1 paper). The work is most often cited by research in Health Informatics (19 citations), Artificial Intelligence (154 citations), Safety Research (29 citations), Computer Vision and Pattern Recognition (25 citations) and Signal Processing (13 citations). John Aslanides has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Trevor Cai, Ethan Perez, Francis Song, Geoffrey Irving, Amelia Glaese, Roman Ring, Saffron Huang, Albin Cassirer, Ian Osband and Aldo Pacchiano. Their work appears in journals such as Proceedings of the AAAI Conference on Artificial Intelligence, Adaptive Agents and Multi-Agents Systems 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.