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
- Reinforcement Learning in Robotics
- Explainable Artificial Intelligence (XAI)
- Privacy-Preserving Technologies in Data
Papers in
-
- Reinforcement Learning in Robotics 3
- Natural Language Processing Techniques 1
- Topic Modeling 1
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- Advanced Bandit Algorithms Research 1
- Auction Theory and Applications 1
- Co-authors
- Roman Ring (1 shared paper)Saffron Huang (1 shared paper)Trevor Cai (1 shared paper)Amelia Glaese (1 shared paper)Geoffrey Irving (1 shared paper)Francis Song (1 shared paper)Ethan Perez (1 shared paper)Ian Osband (1 shared paper)
- Journals
- Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)Neural Information Processing Systems (2 papers)Adaptive Agents and Multi-Agents Systems (1 paper)
- Partner nations
- United KingdomUnited StatesAustralia
In The Last Decade
John Aslanides
4 papers receiving 168 citations
Peers
Comparison fields: 5 of 49
- Health Informatics 17
- Artificial Intelligence 142
- Safety Research 27
- Computer Vision and Pattern Recognition 22
- Management Science and Operations Research 11
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 | 2022 | 128 | |
| 2 | Randomized prior functions for deep reinforcement learning | 2018 | 27 |
| 3 | 2020 | 19 | |
| 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 182 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (3 papers), Natural Language Processing Techniques (1 paper), Economic theories and models (1 paper), Ethics and Social Impacts of AI (1 paper), Advanced Bandit Algorithms Research (1 paper), Topic Modeling (1 paper), Sports Analytics and Performance (1 paper) and Auction Theory and Applications (1 paper). The work is most often cited by research in Health Informatics (17 citations), Artificial Intelligence (142 citations), Safety Research (27 citations), Computer Vision and Pattern Recognition (22 citations) and Management Science and Operations Research (11 citations). John Aslanides has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Roman Ring, Saffron Huang, Trevor Cai, Amelia Glaese, Geoffrey Irving, Francis Song, Ethan Perez, Ian Osband, Albin Cassirer and Aldo Pacchiano. Their work appears in journals such as Proceedings of the AAAI Conference on Artificial Intelligence, Neural Information Processing Systems and Adaptive Agents and Multi-Agents 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.