Robert MacKnight
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Scientific Computing and Data Management
Papers in
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- Bacillus and Francisella bacterial research 1
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- Geochemistry and Geologic Mapping 1
- Law, AI, and Intellectual Property 1
- Co-authors
- Gabriel dos Passos Gomes (3 shared papers)Daniil A. Boiko (2 shared papers)Ben Kline (1 shared paper)Thomas V. Inglesby (1 shared paper)Magda‐Viola Hanke (1 shared paper)W. L. Pickles (1 shared paper)Anita Cicero (1 shared paper)Jaspreet Pannu (1 shared paper)
- Journals
- Nature Computational Science (1 paper)Nature (1 paper)Geosphere (1 paper)PLoS Computational Biology (1 paper)
- Partner nations
- United StatesSwitzerland
In The Last Decade
Robert MacKnight
4 papers receiving 396 citations
Robert MacKnight's Hit Papers
Peers
Comparison fields: 5 of 105
- Health Informatics 30
- Information Systems and Management 45
- Computational Theory and Mathematics 68
- Materials Chemistry 179
- Artificial Intelligence 82
Countries citing papers authored by Robert MacKnight
This map shows the geographic impact of Robert MacKnight'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 MacKnight with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert MacKnight more than expected).
Fields of papers citing papers by Robert MacKnight
This network shows the impact of papers produced by Robert MacKnight. 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 MacKnight. The network helps show where Robert MacKnight may publish in the future.
Co-authors
The 9 scholars most cited alongside Robert MacKnight, 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 | Autonomous chemical research with large language models Hit paper breakdown → | 2023 | 406 |
| 2 | 2025 | 5 | |
| 3 | 2011 | 5 | |
| 4 | 2025 | 3 |
About Robert MacKnight
Robert MacKnight is a scholar working on Molecular Biology, Artificial Intelligence, Materials Chemistry, Geophysics and Computational Theory and Mathematics, having authored 4 papers that have together received 419 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (2 papers), Geochemistry and Geologic Mapping (1 paper), Cell Image Analysis Techniques (1 paper), earthquake and tectonic studies (1 paper), Computational Drug Discovery Methods (1 paper), Bacillus and Francisella bacterial research (1 paper), Geological and Geochemical Analysis (1 paper) and Law, AI, and Intellectual Property (1 paper). The work is most often cited by research in Health Informatics (30 citations), Information Systems and Management (45 citations), Computational Theory and Mathematics (68 citations), Materials Chemistry (179 citations) and Artificial Intelligence (82 citations). Robert MacKnight has collaborated with scholars based in United States and Switzerland. Frequent co-authors include Gabriel dos Passos Gomes, Daniil A. Boiko, Ben Kline, Thomas V. Inglesby, Magda‐Viola Hanke, W. L. Pickles, Anita Cicero, Jaspreet Pannu and Eli A. Silver. Their work appears in journals such as Nature Computational Science, Nature, Geosphere and PLoS Computational Biology.
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.