Andrew J. Ballard
- Molecular Biology
- Materials Chemistry
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Atomic and Molecular Physics, and Optics
- Co-authors
- David J. WalesChristopher JarzynskiChristoph DellagoDebayan ChakrabortyYassmine ChebaroJacob D. StevensonFabio ViolaDharshan Kumaran
- Topics
- Protein Structure and Dynamics (5 papers)Analytical Chemistry and Chromatography (4 papers)Computational Drug Discovery Methods (4 papers)
- Cited by
- Computer Vision and Pattern RecognitionStatistical and Nonlinear PhysicsArtificial Intelligence
- Journals
- Proceedings of the National Academy of SciencesPhysical Review LettersAngewandte Chemie International Edition
- Partner nations
- United KingdomUnited StatesIraq
In The Last Decade
Andrew J. Ballard
17 papers receiving 515 citations
Peers
Comparison fields: 5 of 97
- Molecular Biology 185
- Materials Chemistry 126
- Artificial Intelligence 117
- Computer Vision and Pattern Recognition 103
- Atomic and Molecular Physics, and Optics 99
Countries citing papers authored by Andrew J. Ballard
This map shows the geographic impact of Andrew J. Ballard'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 Andrew J. Ballard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew J. Ballard more than expected).
Fields of papers citing papers by Andrew J. Ballard
This network shows the impact of papers produced by Andrew J. Ballard. 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 Andrew J. Ballard. The network helps show where Andrew J. Ballard may publish in the future.
Co-authorship network of co-authors of Andrew J. Ballard
This figure shows the co-authorship network connecting the top 25 collaborators of Andrew J. Ballard. A scholar is included among the top collaborators of Andrew J. Ballard 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 Andrew J. Ballard. Andrew J. Ballard 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 | 3 | |
| 3 | 2 | |
| 4 | 12 | |
| 5 | 11 | |
| 6 | 12 | |
| 7 | 53 | |
| 8 | 5 | |
| 9 | 19 | |
| 10 | 173 | |
| 11 | 82 | |
| 12 | 1 | |
| 13 | 14 | |
| 14 | 10 | |
| 15 | 55 | |
| 16 | 13 | |
| 17 | 20 | |
| 18 | 50 |
About Andrew J. Ballard
Andrew J. Ballard is a scholar working on Spectroscopy, Condensed Matter Physics and Computational Theory and Mathematics, having authored 18 papers that have together received 535 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (5 papers), Analytical Chemistry and Chromatography (4 papers) and Computational Drug Discovery Methods (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (103 citations), Statistical and Nonlinear Physics (57 citations) and Artificial Intelligence (117 citations). Andrew J. Ballard has collaborated with scholars based in United Kingdom, United States and Iraq. Frequent co-authors include David J. Wales, Christopher Jarzynski, Christoph Dellago, Debayan Chakraborty, Yassmine Chebaro, Jacob D. Stevenson, Fabio Viola, Dharshan Kumaran, Hubert Soyer and Raia Hadsell. Their work appears in journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Angewandte Chemie International Edition.
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.