Martin Uhrin

1.1k total citations · 1 hit paper
7 papers, 726 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 726 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 Machine Learning in Materials Science (3 papers), Scientific Computing and Data Management (3 papers) and Distributed and Parallel Computing Systems (2 papers). Martin Uhrin is often cited by papers focused on Machine Learning in Materials Science (3 papers), Scientific Computing and Data Management (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 Chris J. Pickard, Georg Schusteritsch, Nicola Marzari, Sebastiaan P. Huber, Giovanni Pizzi, Ju‐Song Yu, Casper Welzel Andersen, Spyros Zoupanos, Fernando Gargiulo and Carl S. Adorf 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 701 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Materials Cloud, a platform for open computational science

2020 267 citations Leopold Talirz, Aliaksandr V. Yakutovich et al. Repository for Publications and Research Data (ETH Zurich) profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Martin Uhrin Switzerland	6	574	218	80	75	70	7	726
Miriam Brafman United States	3	605 1.1×	322 1.5×	69 0.9×	80 1.1×	49 0.7×	3	910
Casper Welzel Andersen Denmark	7	488 0.9×	124 0.6×	65 0.8×	54 0.7×	45 0.6×	11	623
Nathan J. Szymanski United States	18	807 1.4×	380 1.7×	140 1.8×	70 0.9×	44 0.6×	35	1.2k
Sebastiaan P. Huber Switzerland	10	411 0.7×	117 0.5×	63 0.8×	34 0.5×	64 0.9×	16	543
Rishi E. Kumar United States	9	558 1.0×	483 2.2×	85 1.1×	102 1.4×	33 0.5×	22	896
Guido Petretto Belgium	13	712 1.2×	326 1.5×	63 0.8×	148 2.0×	96 1.4×	29	1.0k
Steven B. Torrisi United States	12	463 0.8×	171 0.8×	61 0.8×	92 1.2×	119 1.7×	21	619
Carl S. Adorf United States	9	408 0.7×	105 0.5×	85 1.1×	23 0.3×	72 1.0×	13	570
Cyrille Lavigne Canada	9	377 0.7×	222 1.0×	80 1.0×	32 0.4×	86 1.2×	15	680
Fernando Gargiulo Switzerland	8	571 1.0×	216 1.0×	71 0.9×	31 0.4×	168 2.4×	9	642

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

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Uhrin, Martin, et al.. (2025). Machine learning Hubbard parameters with equivariant neural networks. npj Computational Materials. 11(1). 19–19. 13 indexed citations

2.

Clark, Simon, Francesca L. Bleken, Eibar Flores, et al.. (2021). Toward a Unified Description of Battery Data. Advanced Energy Materials. 12(17). 65 indexed citations

3.

Uhrin, Martin & Sebastiaan P. Huber. (2020). . Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU). 1 indexed citations

4.

Uhrin, Martin, Sebastiaan P. Huber, Ju‐Song Yu, Nicola Marzari, & Giovanni Pizzi. (2020). Workflows in AiiDA: Engineering a high-throughput, event-based engine for robust and modular computational workflows. Computational Materials Science. 187. 110086–110086. 106 indexed citations

5.

Talirz, Leopold, Aliaksandr V. Yakutovich, V. Granata, et al.. (2020). Materials Cloud, a platform for open computational science. Repository for Publications and Research Data (ETH Zurich). 267 indexed citations breakdown →

6.

Schusteritsch, Georg, Martin Uhrin, & Chris J. Pickard. (2016). Single-Layered Hittorf’s Phosphorus: A Wide-Bandgap High Mobility 2D Material. Nano Letters. 16(5). 2975–2980. 240 indexed citations

7.

Ackland, Graeme J., et al.. (2011). The MOLDY short-range molecular dynamics package. Computer Physics Communications. 182(12). 2587–2604. 34 indexed citations

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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