Albert Musaelian
- Materials Chemistry top 5%
- Computational Theory and Mathematics top 1%
- Molecular Biology
- Electrical and Electronic Engineering
- Atomic and Molecular Physics, and Optics top 10%
- Co-authors
- Boris KozinskySimon BatznerLixin SunMordechai KornbluthNicola MolinariJonathan P. MailoaMario GeigerTess Smidt
- Topics
- Machine Learning in Materials Science (12 papers)Protein Structure and Dynamics (5 papers)Topic Modeling (3 papers)
- Journals
- Journal of the American Chemical SocietyNature CommunicationsThe Journal of Chemical Physics
- Partner nations
- United StatesUnited KingdomSwitzerland
In The Last Decade
Albert Musaelian
11 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 72
- Materials Chemistry 1.4k
- Computational Theory and Mathematics 449
- Molecular Biology 319
- Electrical and Electronic Engineering 271
- Atomic and Molecular Physics, and Optics 188
Countries citing papers authored by Albert Musaelian
This map shows the geographic impact of Albert Musaelian'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 Albert Musaelian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Albert Musaelian more than expected).
Fields of papers citing papers by Albert Musaelian
This network shows the impact of papers produced by Albert Musaelian. 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 Albert Musaelian. The network helps show where Albert Musaelian may publish in the future.
Co-authorship network of co-authors of Albert Musaelian
This figure shows the co-authorship network connecting the top 25 collaborators of Albert Musaelian. A scholar is included among the top collaborators of Albert Musaelian 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 Albert Musaelian. Albert Musaelian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 9 | |
| 3 | 0 | |
| 4 | The design space of E(3)-equivariant atom-centred interatomic potentialsbreakdown → | 61 |
| 5 | 11 | |
| 6 | 20 | |
| 7 | 23 | |
| 8 | Learning local equivariant representations for large-scale atomistic dynamicsbreakdown → | 370 |
| 9 | 21 | |
| 10 | 24 | |
| 11 | 49 | |
| 12 | E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentialsbreakdown → | 1022 |
| 13 | 57 |
About Albert Musaelian
Albert Musaelian is a scholar working on Materials Chemistry, Electrochemistry and Catalysis, having authored 13 papers that have together received 1.7k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (12 papers), Protein Structure and Dynamics (5 papers) and Topic Modeling (3 papers). The work is most often cited by research in Materials Chemistry (1.4k citations), Computational Theory and Mathematics (449 citations) and Catalysis (110 citations). Albert Musaelian has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Boris Kozinsky, Simon Batzner, Lixin Sun, Mordechai Kornbluth, Nicola Molinari, Jonathan P. Mailoa, Mario Geiger, Tess Smidt, Anders Johansson and Cameron J. Owen. Their work appears in journals such as Journal of the American Chemical Society, Nature Communications and The Journal of Chemical Physics.
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.