Martin Čuma

2.0k total citations
64 papers, 1.6k citations indexed

About

Martin Čuma is a scholar working on Geophysics, Ocean Engineering and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Martin Čuma has authored 64 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Geophysics, 21 papers in Ocean Engineering and 19 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Martin Čuma's work include Geophysical and Geoelectrical Methods (45 papers), Geophysical Methods and Applications (20 papers) and Seismic Imaging and Inversion Techniques (16 papers). Martin Čuma is often cited by papers focused on Geophysical and Geoelectrical Methods (45 papers), Geophysical Methods and Applications (20 papers) and Seismic Imaging and Inversion Techniques (16 papers). Martin Čuma collaborates with scholars based in United States, United Kingdom and Australia. Martin Čuma's co-authors include Steve Scheiner, Michael S. Zhdanov, Gregory A. Voth, Udo W. Schmitt, Tapas Kar, Feng Liu, Alexander V. Soudackov, Tyler Day, Guang-Hong Lu and Glenn A. Wilson and has published in prestigious journals such as Journal of the American Chemical Society, Physical Review Letters and The Journal of Chemical Physics.

In The Last Decade

Martin Čuma

62 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Martin Čuma United States 21 580 470 288 267 236 64 1.6k
Detlef Hohl United States 22 755 1.3× 552 1.2× 329 1.1× 591 2.2× 152 0.6× 66 1.9k
Sebastian Büsch Germany 23 396 0.7× 243 0.5× 261 0.9× 445 1.7× 93 0.4× 81 1.6k
Julian Vrbancich Australia 17 361 0.6× 282 0.6× 217 0.8× 150 0.6× 137 0.6× 71 1.1k
H. H. Nelson United States 25 630 1.1× 159 0.3× 158 0.5× 535 2.0× 105 0.4× 85 1.7k
David Eugene Smith United States 23 1.5k 2.6× 86 0.2× 89 0.3× 547 2.0× 603 2.6× 34 3.1k
Alexander Wolf Germany 20 1.7k 2.9× 86 0.2× 77 0.3× 568 2.1× 280 1.2× 55 2.7k
Howard L. Fang United States 25 449 0.8× 42 0.1× 86 0.3× 461 1.7× 180 0.8× 41 1.7k
H. A. Buckmaster Canada 19 472 0.8× 58 0.1× 102 0.4× 884 3.3× 125 0.5× 130 2.2k
M. K. Paul India 19 72 0.1× 192 0.4× 80 0.3× 235 0.9× 85 0.4× 65 997
Poorna C. Pal United States 13 515 0.9× 235 0.5× 35 0.1× 410 1.5× 55 0.2× 37 1.2k

Countries citing papers authored by Martin Čuma

Since Specialization
Citations

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

Fields of papers citing papers by Martin Čuma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Čuma

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

All Works

20 of 20 papers shown
1.
Zhdanov, Michael S., et al.. (2022). Cooperative inversion of multiphysics data using joint minimum entropy constraints. Near Surface Geophysics. 20(6). 623–636. 10 indexed citations
2.
Zhdanov, Michael S., et al.. (2016). Large-scale seismically guided anisotropic inversion of towed-streamer EM data in the Barents Sea. First Break. 34(11). 1 indexed citations
3.
Jorgensen, Michael R., Martin Čuma, & Michael S. Zhdanov. (2015). 3D joint inversion of magnetotelluric and magnetovariational data to image conductive anomalies in Southern Alberta, Canada. 990–995. 2 indexed citations
4.
Zhdanov, Michael S., et al.. (2015). Inversion of TMI data for the magnetization vector using Gramian constraints. 1602–1606. 13 indexed citations
5.
Edalatpour, Sheila, et al.. (2015). Convergence analysis of the thermal discrete dipole approximation. Physical Review E. 91(6). 63307–63307. 40 indexed citations
6.
Zhdanov, Michael S., et al.. (2014). Anisotropic 3D inversion of towed-streamer electromagnetic data: Case study from the Troll West Oil Province. Interpretation. 2(3). SH97–SH113. 26 indexed citations
7.
Čuma, Martin, Michael S. Zhdanov, & Alexander Gribenko. (2013). Large-scale 3D integral equation based inversion of EarthScope MT data using a variable sensitivity domain. 1. 695–700.
8.
Fraser, Stephen, Glenn A. Wilson, Leif H. Cox, et al.. (2012). Self-organizing maps for pseudo-lithological classification of 3D airborne electromagnetic, gravity gradiometry and magnetic inversions. ASEG Extended Abstracts. 2012(1). 1–4. 18 indexed citations
9.
Wilson, Glenn A., Leif H. Cox, Martin Čuma, & Michael S. Zhdanov. (2012). Inverting airborne geophysical data for mega-cell and giga-cell 3D Earth models. The Leading Edge. 31(3). 316–321. 9 indexed citations
10.
Zhdanov, Michael S., et al.. (2011). Large-scale 3D inversion of marine magnetotelluric data: Case study from the Gemini prospect, Gulf of Mexico. Geophysics. 76(1). F77–F87. 40 indexed citations
11.
12.
Wilson, Glenn A., Martin Čuma, & Michael S. Zhdanov. (2011). Large-scale 3D Inversion of Airborne Potential Field Data. Proceedings. 3 indexed citations
13.
Zhdanov, Michael S., Robert B. Smith, Alexander Gribenko, Martin Čuma, & Marie Green. (2011). Three-dimensional inversion of large-scale EarthScope magnetotelluric data based on the integral equation method: Geoelectrical imaging of the Yellowstone conductive mantle plume. Geophysical Research Letters. 38(8). n/a–n/a. 43 indexed citations
14.
15.
Zhdanov, Michael S., et al.. (2009). Rigorous 3D inversion of marine magnetotelluric data in the area with complex bathymetry. 729–733. 6 indexed citations
16.
Bazterra, V., Martin Čuma, Marta B. Ferraro, & Julio C. Facelli. (2004). A general framework to understand parallel performance in heterogeneous clusters: analysis of a new adaptive parallel genetic algorithm. Journal of Parallel and Distributed Computing. 65(1). 48–57. 22 indexed citations
17.
Huang, Min, Martin Čuma, & Feng Liu. (2003). Seeing the Atomic Orbital: First-Principles Study of the Effect of Tip Geometry on Atomic Force Microscopy. APS March Meeting Abstracts. 2003. 1 indexed citations
18.
Huang, Minghuang, Martin Čuma, & Feng Liu. (2003). Seeing the Atomic Orbital: First-Principles Study of the Effect of Tip Termination on Atomic Force Microscopy. Physical Review Letters. 90(25). 256101–256101. 28 indexed citations
19.
Čuma, Martin, Udo W. Schmitt, & Gregory A. Voth. (2001). A Multi-State Empirical Valence Bond Model for Weak Acid Dissociation in Aqueous Solution. The Journal of Physical Chemistry A. 105(12). 2814–2823. 66 indexed citations
20.
Čuma, Martin, Steve Scheiner, & Tapas Kar. (1998). Competition between Rotamerization and Proton Transfer in o-Hydroxybenzaldehyde. Journal of the American Chemical Society. 120(40). 10497–10503. 44 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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