Adil Kabylda
- Materials Chemistry
- Molecular Biology
- Computational Theory and Mathematics top 10%
- Organic Chemistry
- Atomic and Molecular Physics, and Optics
- Co-authors
- Alexandre TkatchenkoStefan ChmielaValentín Vassilev-GalindoOliver T. UnkeHuziel E. SaucedaKlaus‐Robert MüllerIgor PoltavskyYongxin Li
- Topics
- Machine Learning in Materials Science (5 papers)Computational Drug Discovery Methods (4 papers)Photoreceptor and optogenetics research (3 papers)
- Partner nations
- RussiaGermanyLuxembourg
In The Last Decade
Adil Kabylda
12 papers receiving 213 citations
Hit Papers
Peers
Comparison fields: 5 of 42
- Materials Chemistry 132
- Molecular Biology 66
- Computational Theory and Mathematics 64
- Organic Chemistry 41
- Atomic and Molecular Physics, and Optics 24
Countries citing papers authored by Adil Kabylda
This map shows the geographic impact of Adil Kabylda'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 Adil Kabylda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adil Kabylda more than expected).
Fields of papers citing papers by Adil Kabylda
This network shows the impact of papers produced by Adil Kabylda. 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 Adil Kabylda. The network helps show where Adil Kabylda may publish in the future.
Co-authorship network of co-authors of Adil Kabylda
This figure shows the co-authorship network connecting the top 25 collaborators of Adil Kabylda. A scholar is included among the top collaborators of Adil Kabylda 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 Adil Kabylda. Adil Kabylda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 13 | |
| 3 | 6 | |
| 4 | Accurate global machine learning force fields for molecules with hundreds of atomsbreakdown → | 112 |
| 5 | 19 | |
| 6 | 3 | |
| 7 | 9 | |
| 8 | 2 | |
| 9 | 11 | |
| 10 | 23 | |
| 11 | 10 | |
| 12 | 4 |
About Adil Kabylda
Adil Kabylda is a scholar working on Computational Theory and Mathematics, Physical and Theoretical Chemistry and Biophysics, having authored 12 papers that have together received 218 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (5 papers), Computational Drug Discovery Methods (4 papers) and Photoreceptor and optogenetics research (3 papers). The work is most often cited by research in Computational Theory and Mathematics (64 citations), Materials Chemistry (132 citations) and Biophysics (15 citations). Adil Kabylda has collaborated with scholars based in Russia, Germany and Luxembourg. Frequent co-authors include Alexandre Tkatchenko, Stefan Chmiela, Valentín Vassilev-Galindo, Oliver T. Unke, Huziel E. Sauceda, Klaus‐Robert Müller, Igor Poltavsky, Yongxin Li, Valentine G. Nenajdenko and Dasheng Leow. Their work appears in journals such as Journal of the American Chemical Society, Nature Communications and Advanced Functional 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.