Ryan‐Rhys Griffiths
Impact in
-
- Computational Drug Discovery Methods
- Advanced Multi-Objective Optimization Algorithms
-
- Machine Learning in Materials Science
- Photochromic and Fluorescence Chemistry
Papers in
-
- Computational Drug Discovery Methods 3
- Advanced Multi-Objective Optimization Algorithms 2
-
- Machine Learning and Algorithms 4
- Co-authors
- José Miguel Hernández-Lobato (1 shared paper)Noam Bernstein (1 shared paper)Simon Wengert (1 shared paper)Johannes T. Margraf (1 shared paper)Gábor Cśanyi (1 shared paper)Karsten Reuter (1 shared paper)Christian Künkel (1 shared paper)Volker L. Deringer (1 shared paper)
- Journals
- Chemical Science (2 papers)Accounts of Chemical Research (1 paper)Journal of Electroanalytical Chemistry (1 paper)Journal of Machine Learning Research (1 paper)Journal of Artificial Intelligence Research (1 paper)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Ryan‐Rhys Griffiths
14 papers receiving 452 citations
Peers
Comparison fields: 5 of 85
- Computational Theory and Mathematics 187
- Materials Chemistry 245
- Artificial Intelligence 74
- Structural Biology 3
- Astronomy and Astrophysics 33
Countries citing papers authored by Ryan‐Rhys Griffiths
This map shows the geographic impact of Ryan‐Rhys Griffiths'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 Ryan‐Rhys Griffiths with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryan‐Rhys Griffiths more than expected).
Fields of papers citing papers by Ryan‐Rhys Griffiths
This network shows the impact of papers produced by Ryan‐Rhys Griffiths. 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 Ryan‐Rhys Griffiths. The network helps show where Ryan‐Rhys Griffiths may publish in the future.
Co-authors
The 25 scholars most cited alongside Ryan‐Rhys Griffiths, 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 | 2019 | 219 | |
| 2 | 2020 | 89 | |
| 3 | 2022 | 46 | |
| 4 | 2022 | 28 | |
| 5 | 1979 | 21 | |
| 6 | 2023 | 17 | |
| 7 | 2021 | 17 | |
| 8 | 2019 | 15 | |
| 9 | 2024 | 2 | |
| 10 | 2022 | 2 | |
| 11 | Are We Forgetting about Compositional Optimisers in Bayesian Optimisation | 2021 | 1 |
| 12 | 2023 | 1 | |
| 13 | 2020 | 1 | |
| 14 | 2019 | 1 |
About Ryan‐Rhys Griffiths
Ryan‐Rhys Griffiths is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Materials Chemistry, Astronomy and Astrophysics and Atomic and Molecular Physics, and Optics, having authored 14 papers that have together received 460 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (4 papers), Computational Drug Discovery Methods (3 papers), Machine Learning in Materials Science (3 papers), Advanced Bandit Algorithms Research (2 papers), Advanced Multi-Objective Optimization Algorithms (2 papers), Astrophysical Phenomena and Observations (2 papers), Advanced biosensing and bioanalysis techniques (1 paper) and Catalysis and Oxidation Reactions (1 paper). The work is most often cited by research in Computational Theory and Mathematics (187 citations), Materials Chemistry (245 citations), Artificial Intelligence (74 citations), Structural Biology (3 citations) and Astronomy and Astrophysics (33 citations). Ryan‐Rhys Griffiths has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include José Miguel Hernández-Lobato, Noam Bernstein, Simon Wengert, Johannes T. Margraf, Gábor Cśanyi, Karsten Reuter, Christian Künkel, Volker L. Deringer, Bingqing Cheng and Bonan Zhu. Their work appears in journals such as Chemical Science, Accounts of Chemical Research, Journal of Electroanalytical Chemistry, Journal of Machine Learning Research and Journal of Artificial Intelligence Research.
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.