Alexander Matthews
- Artificial Intelligence top 10%
- Control and Systems Engineering
- Computational Theory and Mathematics
- Infectious Diseases
- Computer Vision and Pattern Recognition
- Co-authors
- Zoubin GhahramaniJames HensmanRichard E. TurnerMaurizio FilipponeSalvador AmaralSusana Vaz NeryJoshua FrancisK. Cranmer
- Topics
- Gaussian Processes and Bayesian Inference (4 papers)Dermatological diseases and infestations (3 papers)Advanced Multi-Objective Optimization Algorithms (3 papers)
- Journals
- BMC Public HealthAmerican Journal of Tropical Medicine and HygieneTransactions of the Royal Society of Tropical Medicine and Hygiene
- Partner nations
- United KingdomAustraliaTimor-Leste
In The Last Decade
Alexander Matthews
16 papers receiving 286 citations
Peers
Comparison fields: 5 of 97
- Artificial Intelligence 156
- Control and Systems Engineering 40
- Computational Theory and Mathematics 35
- Infectious Diseases 34
- Computer Vision and Pattern Recognition 31
Countries citing papers authored by Alexander Matthews
This map shows the geographic impact of Alexander Matthews'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 Alexander Matthews with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander Matthews more than expected).
Fields of papers citing papers by Alexander Matthews
This network shows the impact of papers produced by Alexander Matthews. 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 Alexander Matthews. The network helps show where Alexander Matthews may publish in the future.
Co-authorship network of co-authors of Alexander Matthews
This figure shows the co-authorship network connecting the top 25 collaborators of Alexander Matthews. A scholar is included among the top collaborators of Alexander Matthews based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Alexander Matthews. Alexander Matthews is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 10 | |
| 3 | 19 | |
| 4 | 10 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 14 | |
| 9 | 10 | |
| 10 | 10 | |
| 11 | 4 | |
| 12 | 1 | |
| 13 | Functional Regularisation for Continual Learning with Gaussian Processes | 9 |
| 14 | 27 | |
| 15 | 22 | |
| 16 | 152 | |
| 17 | 7 |
About Alexander Matthews
Alexander Matthews is a scholar working on Parasitology, Applied Microbiology and Biotechnology and Family Practice, having authored 17 papers that have together received 298 indexed citations. Recurring topics across this work include Gaussian Processes and Bayesian Inference (4 papers), Dermatological diseases and infestations (3 papers) and Advanced Multi-Objective Optimization Algorithms (3 papers). The work is most often cited by research in Artificial Intelligence (156 citations), Computational Mathematics (2 citations) and Parasitology (22 citations). Alexander Matthews has collaborated with scholars based in United Kingdom, Australia and Timor-Leste. Frequent co-authors include Zoubin Ghahramani, James Hensman, Richard E. Turner, Maurizio Filippone, Salvador Amaral, Susana Vaz Nery, Joshua Francis, K. Cranmer, Michael S. Albergo and Jonathan Schwarz. Their work appears in journals such as BMC Public Health, American Journal of Tropical Medicine and Hygiene and Transactions of the Royal Society of Tropical Medicine and Hygiene.
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.