Philippe Schwaller
Impact in
- Computational Theory and Mathematics top 0.2%
- Computational Drug Discovery Methods
- Materials Chemistry top 1%
- Machine Learning in Materials Science
- 2D Materials and Applications
- Graphene research and applications
- MXene and MAX Phase Materials
Papers in
-
- Machine Learning in Materials Science 38
-
- Computational Drug Discovery Methods 30
- Co-authors
- Teodoro Laino (22 shared papers)Jean‐Louis Reymond (7 shared papers)Alain C. Vaucher (12 shared papers)Ivano E. Castelli (1 shared paper)Nicolas Mounet (1 shared paper)Andrius Merkys (1 shared paper)Nicola Marzari (1 shared paper)Marco Gibertini (1 shared paper)
- Journals
- Nature Communications (5 papers)Nature Machine Intelligence (5 papers)Chemical Science (4 papers)CHIMIA International Journal for Chemistry (4 papers)Journal of the American Chemical Society (3 papers)
- Partner nations
- SwitzerlandUnited StatesUnited Kingdom
In The Last Decade
Philippe Schwaller
49 papers receiving 4.1k citations
Philippe Schwaller's Hit Papers
Peers
Comparison fields: 5 of 138
- Computational Theory and Mathematics 1.3k
- Materials Chemistry 3.0k
- Catalysis 125
- Health Informatics 22
- Inorganic Chemistry 191
Countries citing papers authored by Philippe Schwaller
This map shows the geographic impact of Philippe Schwaller'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 Philippe Schwaller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philippe Schwaller more than expected).
Fields of papers citing papers by Philippe Schwaller
This network shows the impact of papers produced by Philippe Schwaller. 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 Philippe Schwaller. The network helps show where Philippe Schwaller may publish in the future.
Co-authors
The 25 scholars most cited alongside Philippe Schwaller, 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 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Two-dimensional materials from high-throughput computational exfoliation of experimentally known compounds Hit paper breakdown → | 2018 | 1400 |
| 2 | Augmenting large language models with chemistry tools Hit paper breakdown → | 2024 | 336 |
| 3 | 2018 | 296 | |
| 4 | 2020 | 264 | |
| 5 | Leveraging large language models for predictive chemistry Hit paper breakdown → | 2024 | 217 |
| 6 | 2021 | 213 | |
| 7 | 2021 | 180 | |
| 8 | 2021 | 177 | |
| 9 | 2020 | 138 | |
| 10 | 2020 | 138 | |
| 11 | 2022 | 107 | |
| 12 | 2020 | 103 | |
| 13 | Machine learning-aided generative molecular design Hit paper breakdown → | 2024 | 88 |
| 14 | 2022 | 66 | |
| 15 | 2021 | 55 | |
| 16 | 2021 | 54 | |
| 17 | 2023 | 43 | |
| 18 | 2023 | 33 | |
| 19 | 2023 | 29 | |
| 20 | Targeting protein–ligand neosurfaces with a generalizable deep learning tool Hit paper breakdown → | 2025 | 28 |
About Philippe Schwaller
Philippe Schwaller is a scholar working on Materials Chemistry, Computational Theory and Mathematics, Artificial Intelligence, Molecular Biology and Biomedical Engineering, having authored 56 papers that have together received 4.2k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (38 papers), Computational Drug Discovery Methods (30 papers), Topic Modeling (8 papers), Chemistry and Chemical Engineering (4 papers), Innovative Microfluidic and Catalytic Techniques Innovation (4 papers), Machine Learning in Bioinformatics (3 papers), Chemical Synthesis and Analysis (3 papers) and Advanced Text Analysis Techniques (3 papers). The work is most often cited by research in Computational Theory and Mathematics (1.3k citations), Materials Chemistry (3.0k citations), Catalysis (125 citations), Health Informatics (22 citations) and Inorganic Chemistry (191 citations). Philippe Schwaller has collaborated with scholars based in Switzerland, United States and United Kingdom. Frequent co-authors include Teodoro Laino, Jean‐Louis Reymond, Alain C. Vaucher, Ivano E. Castelli, Nicolas Mounet, Andrius Merkys, Nicola Marzari, Marco Gibertini, Andrea Cepellotti and Antimo Marrazzo. Their work appears in journals such as Nature Communications, Nature Machine Intelligence, Chemical Science, CHIMIA International Journal for Chemistry and Journal of the American Chemical Society.
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.