Gary Tom
Impact in
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- Machine Learning in Materials Science
- Graphene research and applications
- Luminescence and Fluorescent Materials
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- Computational Drug Discovery Methods
Papers in
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- Machine Learning in Materials Science 6
- Luminescence and Fluorescent Materials 2
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- Computational Drug Discovery Methods 7
- Co-authors
- Alán Aspuru‐Guzik (7 shared papers)Sergio Pablo‐García (3 shared papers)Ella Miray Rajaonson (3 shared papers)Han Hao (2 shared papers)Samantha Corapi (2 shared papers)Stanley Lo (4 shared papers)Sarah A. Burke (5 shared papers)Martin Seifrid (2 shared papers)
- Journals
- Journal of the American Chemical Society (1 paper)Chemistry of Materials (1 paper)Nature Communications (1 paper)The Journal of Physical Chemistry C (1 paper)Science Advances (1 paper)
- Partner nations
- CanadaUnited StatesSweden
In The Last Decade
Gary Tom
15 papers receiving 451 citations
Gary Tom's Hit Papers
Peers
Comparison fields: 5 of 77
- Materials Chemistry 256
- Computational Theory and Mathematics 71
- Information Systems and Management 20
- Atomic and Molecular Physics, and Optics 71
- Biomedical Engineering 92
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
| # | Work | ||
|---|---|---|---|
| 1 | Self-Driving Laboratories for Chemistry and Materials Science Hit paper breakdown → | 2024 | 198 |
| 2 | 2019 | 71 | |
| 3 | 2024 | 38 | |
| 4 | 2021 | 34 | |
| 5 | 2023 | 23 | |
| 6 | 2022 | 23 | |
| 7 | 2025 | 13 | |
| 8 | 2024 | 13 | |
| 9 | 2018 | 12 | |
| 10 | 2025 | 9 | |
| 11 | 2024 | 9 | |
| 12 | 2022 | 8 | |
| 13 | 2024 | 7 | |
| 14 | 2025 | 1 | |
| 15 | 2025 | 1 | |
| 16 | 2025 | 0 |
About Gary Tom
Gary Tom is a scholar working on Materials Chemistry, Computational Theory and Mathematics, Biomedical Engineering, Electrical and Electronic Engineering and Molecular Biology, having authored 16 papers that have together received 460 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Machine Learning in Materials Science (6 papers), Molecular Junctions and Nanostructures (3 papers), Luminescence and Fluorescent Materials (2 papers), Surface Chemistry and Catalysis (2 papers), Various Chemistry Research Topics (2 papers), Analytical Chemistry and Chromatography (2 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (2 papers). The work is most often cited by research in Materials Chemistry (256 citations), Computational Theory and Mathematics (71 citations), Information Systems and Management (20 citations), Atomic and Molecular Physics, and Optics (71 citations) and Biomedical Engineering (92 citations). Gary Tom has collaborated with scholars based in Canada, United States and Sweden. Frequent co-authors include Alán Aspuru‐Guzik, Sergio Pablo‐García, Ella Miray Rajaonson, Han Hao, Samantha Corapi, Stanley Lo, Sarah A. Burke, Martin Seifrid, Kourosh Darvish and Naruki Yoshikawa. Their work appears in journals such as Journal of the American Chemical Society, Chemistry of Materials, Nature Communications, The Journal of Physical Chemistry C and Science Advances.
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.