Robert Burbidge
Impact in
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- Computational Drug Discovery Methods
- Analytical Chemistry top 5%
- Spectroscopy and Chemometric Analyses
Papers in
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- Machine Learning and Data Classification 3
- Reinforcement Learning in Robotics 2
- Metaheuristic Optimization Algorithms Research 2
- Neural Networks and Applications 2
- Evolutionary Algorithms and Applications 2
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- Face and Expression Recognition 3
- Co-authors
- Matthew Trotter (2 shared papers)Bernard Buxton (2 shared papers)Sean B. Holden (2 shared papers)Jem J. Rowland (2 shared papers)Ross D. King (2 shared papers)Benjamin J. Whitaker (2 shared papers)
- Journals
- Information Sciences (1 paper)Journal of Modern Optics (1 paper)Lecture notes in computer science (2 papers)Lecture notes in statistics (1 paper)Research Explorer (The University of Manchester) (1 paper)
- Partner nations
- United KingdomAustraliaBelgium
In The Last Decade
Robert Burbidge
9 papers receiving 755 citations
Robert Burbidge's Hit Papers
Peers
Comparison fields: 5 of 125
- Computational Theory and Mathematics 306
- Analytical Chemistry 85
- Artificial Intelligence 201
- Spectroscopy 85
- Molecular Biology 239
Countries citing papers authored by Robert Burbidge
This map shows the geographic impact of Robert Burbidge'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 Robert Burbidge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Burbidge more than expected).
Fields of papers citing papers by Robert Burbidge
This network shows the impact of papers produced by Robert Burbidge. 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 Robert Burbidge. The network helps show where Robert Burbidge may publish in the future.
Co-authors
The 6 scholars most cited alongside Robert Burbidge, 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 | Drug design by machine learning: support vector machines for pharmaceutical data analysis Hit paper breakdown → | 2001 | 575 |
| 2 | 2007 | 124 | |
| 3 | An introduction to support vector machines for data mining | 2001 | 64 |
| 4 | 2009 | 11 | |
| 5 | 2013 | 9 | |
| 6 | 2007 | 9 | |
| 7 | 2003 | 3 | |
| 8 | 2001 | 2 | |
| 9 | 2007 | 1 |
About Robert Burbidge
Robert Burbidge is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Atomic and Molecular Physics, and Optics, Computational Theory and Mathematics and Signal Processing, having authored 9 papers that have together received 798 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (3 papers), Face and Expression Recognition (3 papers), Laser-Matter Interactions and Applications (2 papers), Reinforcement Learning in Robotics (2 papers), Metaheuristic Optimization Algorithms Research (2 papers), Neural Networks and Applications (2 papers), Computational Drug Discovery Methods (2 papers) and Evolutionary Algorithms and Applications (2 papers). The work is most often cited by research in Computational Theory and Mathematics (306 citations), Analytical Chemistry (85 citations), Artificial Intelligence (201 citations), Spectroscopy (85 citations) and Molecular Biology (239 citations). Robert Burbidge has collaborated with scholars based in United Kingdom, Australia and Belgium. Frequent co-authors include Matthew Trotter, Bernard Buxton, Sean B. Holden, Jem J. Rowland, Ross D. King and Benjamin J. Whitaker. Their work appears in journals such as Information Sciences, Journal of Modern Optics, Lecture notes in computer science, Lecture notes in statistics and Research Explorer (The University of Manchester).
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.