Alain C. Vaucher
- Materials Chemistry top 5%
- Computational Theory and Mathematics top 1%
- Molecular Biology
- Biomedical Engineering
- Artificial Intelligence top 10%
- Co-authors
- Teodoro LainoMarkus ReiherPhilippe SchwallerJean‐Louis ReymondVishnu H NairGregor N. C. SimmDaniel ProbstDavid Kreutter
- Topics
- Machine Learning in Materials Science (21 papers)Computational Drug Discovery Methods (12 papers)Topic Modeling (6 papers)
- Partner nations
- SwitzerlandBelgiumUnited Kingdom
In The Last Decade
Alain C. Vaucher
34 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 98
- Materials Chemistry 806
- Computational Theory and Mathematics 517
- Molecular Biology 314
- Biomedical Engineering 177
- Artificial Intelligence 132
Countries citing papers authored by Alain C. Vaucher
This map shows the geographic impact of Alain C. Vaucher'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 Alain C. Vaucher with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alain C. Vaucher more than expected).
Fields of papers citing papers by Alain C. Vaucher
This network shows the impact of papers produced by Alain C. Vaucher. 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 Alain C. Vaucher. The network helps show where Alain C. Vaucher may publish in the future.
Co-authorship network of co-authors of Alain C. Vaucher
This figure shows the co-authorship network connecting the top 25 collaborators of Alain C. Vaucher. A scholar is included among the top collaborators of Alain C. Vaucher 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 Alain C. Vaucher. Alain C. Vaucher is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 15 | |
| 3 | 3 | |
| 4 | 7 | |
| 5 | 14 | |
| 6 | 1 | |
| 7 | 11 | |
| 8 | 26 | |
| 9 | 1 | |
| 10 | 2 | |
| 11 | 61 | |
| 12 | 170 | |
| 13 | 52 | |
| 14 | 200 | |
| 15 | Human-in-the-loop for a Disconnection Aware Retrosynthesis | 1 |
| 16 | 132 | |
| 17 | 1 | |
| 18 | 20 | |
| 19 | 1 | |
| 20 | 45 |
About Alain C. Vaucher
Alain C. Vaucher is a scholar working on Computational Theory and Mathematics, Materials Chemistry and Physical and Theoretical Chemistry, having authored 34 papers that have together received 1.2k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (21 papers), Computational Drug Discovery Methods (12 papers) and Topic Modeling (6 papers). The work is most often cited by research in Computational Theory and Mathematics (517 citations), Materials Chemistry (806 citations) and Catalysis (98 citations). Alain C. Vaucher has collaborated with scholars based in Switzerland, Belgium and United Kingdom. Frequent co-authors include Teodoro Laino, Markus Reiher, Philippe Schwaller, Jean‐Louis Reymond, Vishnu H Nair, Gregor N. C. Simm, Daniel Probst, David Kreutter, Federico Zipoli and David R. Glowacki. Their work appears in journals such as Nature Communications, The Journal of Chemical Physics and Chemistry of Materials.
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.