Martin Uhrin

26 total papers · 1.1k total citations
7 papers, 719 citations indexed

About

Martin Uhrin is a scholar working on Materials Chemistry, Information Systems and Management and Computer Networks and Communications. According to data from OpenAlex, Martin Uhrin has authored 7 papers receiving a total of 719 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Materials Chemistry, 3 papers in Information Systems and Management and 2 papers in Computer Networks and Communications. Recurrent topics in Martin Uhrin's work include Scientific Computing and Data Management (3 papers), Machine Learning in Materials Science (3 papers) and Distributed and Parallel Computing Systems (2 papers). Martin Uhrin is often cited by papers focused on Scientific Computing and Data Management (3 papers), Machine Learning in Materials Science (3 papers) and Distributed and Parallel Computing Systems (2 papers). Martin Uhrin collaborates with scholars based in Switzerland, Denmark and United Kingdom. Martin Uhrin's co-authors include Georg Schusteritsch, Chris J. Pickard, Nicola Marzari, Sebastiaan P. Huber, Giovanni Pizzi, Ju‐Song Yu, Casper Welzel Andersen, T. C. Schulthess, Carlo A. Pignedoli and Joost VandeVondele and has published in prestigious journals such as Nano Letters, Advanced Energy Materials and Computer Physics Communications.

In The Last Decade

Martin Uhrin

7 papers receiving 694 citations

Hit Papers

Materials Cloud, a platfo... 2020 2026 2022 2024 2020 50 100 150 200 250

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Martin Uhrin 567 215 80 75 68 7 719
Miriam Brafman 595 1.0× 320 1.5× 69 0.9× 81 1.1× 49 0.7× 3 899
Hermann Tribukait 459 0.8× 222 1.0× 135 1.7× 98 1.3× 27 0.4× 6 706
Rishi E. Kumar 534 0.9× 471 2.2× 84 1.1× 101 1.3× 32 0.5× 22 862
Fernando Gargiulo 571 1.0× 215 1.0× 71 0.9× 31 0.4× 168 2.5× 9 641
Cyrille Lavigne 371 0.7× 216 1.0× 79 1.0× 30 0.4× 85 1.3× 15 665
Aliaksandr V. Yakutovich 594 1.0× 155 0.7× 139 1.7× 74 1.0× 92 1.4× 12 755
Travis Williams 470 0.8× 93 0.4× 141 1.8× 61 0.8× 16 0.2× 10 708
Lauri Himanen 746 1.3× 159 0.7× 59 0.7× 112 1.5× 73 1.1× 11 849
Ryan Murdock 471 0.8× 115 0.5× 72 0.9× 35 0.5× 19 0.3× 8 666
Kameel Abdel‐Latif 427 0.8× 276 1.3× 248 3.1× 38 0.5× 27 0.4× 13 657

Countries citing papers authored by Martin Uhrin

Since Specialization
Citations

This map shows the geographic impact of Martin Uhrin'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 Martin Uhrin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Uhrin more than expected).

Fields of papers citing papers by Martin Uhrin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martin Uhrin. 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 Martin Uhrin. The network helps show where Martin Uhrin may publish in the future.

Co-authorship network of co-authors of Martin Uhrin

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Uhrin. A scholar is included among the top collaborators of Martin Uhrin 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 Martin Uhrin. Martin Uhrin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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.

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