Gary Tom
Impact in
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- Computational Drug Discovery Methods
- Materials Chemistry top 5%
- Machine Learning in Materials Science
- Graphene research and applications
- Luminescence and Fluorescent Materials
Papers in
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- Computational Drug Discovery Methods 9
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- Machine Learning in Materials Science 11
- Luminescence and Fluorescent Materials 2
- Co-authors
- Alán Aspuru‐Guzik (12 shared papers)Sergio Pablo‐García (3 shared papers)Ella Miray Rajaonson (3 shared papers)Han Hao (2 shared papers)Stanley Lo (4 shared papers)Martin T. Seifrid (2 shared papers)Naruki Yoshikawa (2 shared papers)Samantha Corapi (2 shared papers)
- Journals
- Machine Learning Science and Technology (1 paper)Nature Communications (1 paper)Science Advances (1 paper)Patterns (1 paper)Matter (1 paper)
- Partner nations
- CanadaUnited StatesSwitzerland
In The Last Decade
Gary Tom
23 papers receiving 963 citations
Gary Tom's Hit Papers
Peers
Comparison fields: 5 of 76
- Computational Theory and Mathematics 212
- Materials Chemistry 517
- Drug Discovery 3
- Atomic and Molecular Physics, and Optics 94
- Physical and Theoretical Chemistry 31
Countries citing papers authored by Gary Tom
This map shows the geographic impact of Gary Tom'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 Gary Tom with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gary Tom more than expected).
Fields of papers citing papers by Gary Tom
This network shows the impact of papers produced by Gary Tom. 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 Gary Tom. The network helps show where Gary Tom may publish in the future.
Co-authors
The 25 scholars most cited alongside Gary Tom, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Self-Driving Laboratories for Chemistry and Materials Science Hit paper breakdown → | 2024 | 390 |
| 2 | SELFIES and the future of molecular string representations Hit paper breakdown → | 2022 | 180 |
| 3 | 2019 | 83 | |
| 4 | 2024 | 57 | |
| 5 | 2021 | 38 | |
| 6 | El Agente: An autonomous agent for quantum chemistry Hit paper breakdown → | 2025 | 34 |
| 7 | 2023 | 31 | |
| 8 | 2022 | 27 | |
| 9 | 2025 | 24 | |
| 10 | 2023 | 19 | |
| 11 | 2024 | 19 | |
| 12 | 2018 | 15 | |
| 13 | 2025 | 15 | |
| 14 | 2024 | 13 | |
| 15 | 2024 | 12 | |
| 16 | 2022 | 11 | |
| 17 | 2022 | 10 | |
| 18 | 2025 | 5 | |
| 19 | 2025 | 2 | |
| 20 | 2025 | 2 |
About Gary Tom
Gary Tom is a scholar working on Computational Theory and Mathematics, Materials Chemistry, Sensory Systems, Biomedical Engineering and Management Science and Operations Research, having authored 24 papers that have together received 990 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (11 papers), Computational Drug Discovery Methods (9 papers), Artificial Intelligence Applications (2 papers), Surface Chemistry and Catalysis (2 papers), Advanced Bandit Algorithms Research (2 papers), Luminescence and Fluorescent Materials (2 papers), Advanced Chemical Sensor Technologies (2 papers) and Olfactory and Sensory Function Studies (2 papers). The work is most often cited by research in Computational Theory and Mathematics (212 citations), Materials Chemistry (517 citations), Drug Discovery (3 citations), Atomic and Molecular Physics, and Optics (94 citations) and Physical and Theoretical Chemistry (31 citations). Gary Tom has collaborated with scholars based in Canada, United States and Switzerland. Frequent co-authors include Alán Aspuru‐Guzik, Sergio Pablo‐García, Ella Miray Rajaonson, Han Hao, Stanley Lo, Martin T. Seifrid, Naruki Yoshikawa, Samantha Corapi, Stefan P. Schmid and Yang Cao. Their work appears in journals such as Machine Learning Science and Technology, Nature Communications, Science Advances, Patterns and Matter.
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.