Teodoro Laino
Impact in
- Computational Theory and Mathematics top 0.2%
- Computational Drug Discovery Methods
- Materials Chemistry top 2%
- Machine Learning in Materials Science
- Graphene research and applications
Papers in
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- Machine Learning in Materials Science 31
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- Protein Structure and Dynamics 7
- Chemical Synthesis and Analysis 7
- Co-authors
- Philippe Schwaller (22 shared papers)Alessandro Curioni (17 shared papers)Alain C. Vaucher (20 shared papers)Jean‐Louis Reymond (4 shared papers)Michele Parrinello (6 shared papers)Vishnu H Nair (5 shared papers)Alessandro Laio (3 shared papers)Fawzi Mohamed (2 shared papers)
- Journals
- Nature Communications (5 papers)The Journal of Physical Chemistry B (5 papers)Journal of Chemical Theory and Computation (5 papers)Chemical Science (4 papers)npj Computational Materials (4 papers)
- Partner nations
- SwitzerlandUnited StatesItaly
In The Last Decade
Teodoro Laino
93 papers receiving 4.3k citations
Teodoro Laino's Hit Papers
Peers
Comparison fields: 5 of 139
- Computational Theory and Mathematics 1.1k
- Materials Chemistry 2.2k
- Physical and Theoretical Chemistry 259
- Biophysics 120
- Molecular Biology 1.2k
Countries citing papers authored by Teodoro Laino
This map shows the geographic impact of Teodoro Laino'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 Teodoro Laino with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Teodoro Laino more than expected).
Fields of papers citing papers by Teodoro Laino
This network shows the impact of papers produced by Teodoro Laino. 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 Teodoro Laino. The network helps show where Teodoro Laino may publish in the future.
Co-authors
The 25 scholars most cited alongside Teodoro Laino, 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 96 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 377 | |
| 2 | 2018 | 296 | |
| 3 | Accelerating materials discovery using artificial intelligence, high performance computing and robotics Hit paper breakdown → | 2022 | 267 |
| 4 | 2020 | 264 | |
| 5 | 2005 | 232 | |
| 6 | 2014 | 215 | |
| 7 | 2021 | 213 | |
| 8 | 2021 | 180 | |
| 9 | 2021 | 177 | |
| 10 | 2020 | 138 | |
| 11 | 2020 | 138 | |
| 12 | 2006 | 135 | |
| 13 | 2020 | 103 | |
| 14 | 2012 | 90 | |
| 15 | 2022 | 81 | |
| 16 | 2003 | 80 | |
| 17 | 2022 | 66 | |
| 18 | 2011 | 65 | |
| 19 | 2008 | 59 | |
| 20 | 2011 | 56 |
About Teodoro Laino
Teodoro Laino is a scholar working on Materials Chemistry, Molecular Biology, Computational Theory and Mathematics, Biomedical Engineering and Electrical and Electronic Engineering, having authored 96 papers that have together received 4.4k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (31 papers), Computational Drug Discovery Methods (19 papers), Topic Modeling (8 papers), Advanced Chemical Physics Studies (7 papers), Protein Structure and Dynamics (7 papers), Chemical Synthesis and Analysis (7 papers), Advancements in Battery Materials (6 papers) and Advanced Battery Materials and Technologies (6 papers). The work is most often cited by research in Computational Theory and Mathematics (1.1k citations), Materials Chemistry (2.2k citations), Physical and Theoretical Chemistry (259 citations), Biophysics (120 citations) and Molecular Biology (1.2k citations). Teodoro Laino has collaborated with scholars based in Switzerland, United States and Italy. Frequent co-authors include Philippe Schwaller, Alessandro Curioni, Alain C. Vaucher, Jean‐Louis Reymond, Michele Parrinello, Vishnu H Nair, Alessandro Laio, Fawzi Mohamed, Costas Bekas and Katharina Meier. Their work appears in journals such as Nature Communications, The Journal of Physical Chemistry B, Journal of Chemical Theory and Computation, Chemical Science and npj Computational 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.