Martha A. Gallivan
- Computational Mechanics top 10%
- Polymers and Plastics
- Materials Chemistry
- Electrical and Electronic Engineering
- Biomedical Engineering
- Co-authors
- Richard M. MurrayCihan OguzJohn G. GeorgiadisRichard O. BuckiusDavid R. NobleTimothy E. LongSerkan ÜnalEmel Yılgör
- Topics
- Model Reduction and Neural Networks (7 papers)Theoretical and Computational Physics (4 papers)Dendrimers and Hyperbranched Polymers (3 papers)
- Partner nations
- United StatesTürkiyeMexico
In The Last Decade
Martha A. Gallivan
25 papers receiving 366 citations
Peers
Comparison fields: 5 of 69
- Computational Mechanics 136
- Polymers and Plastics 95
- Materials Chemistry 80
- Electrical and Electronic Engineering 63
- Biomedical Engineering 56
Countries citing papers authored by Martha A. Gallivan
This map shows the geographic impact of Martha A. Gallivan'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 Martha A. Gallivan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martha A. Gallivan more than expected).
Fields of papers citing papers by Martha A. Gallivan
This network shows the impact of papers produced by Martha A. Gallivan. 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 Martha A. Gallivan. The network helps show where Martha A. Gallivan may publish in the future.
Co-authorship network of co-authors of Martha A. Gallivan
This figure shows the co-authorship network connecting the top 25 collaborators of Martha A. Gallivan. A scholar is included among the top collaborators of Martha A. Gallivan 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 Martha A. Gallivan. Martha A. Gallivan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 16 | |
| 2 | 10 | |
| 3 | 1 | |
| 4 | 28 | |
| 5 | 3 | |
| 6 | 65 | |
| 7 | 6 | |
| 8 | 5 | |
| 9 | 11 | |
| 10 | 12 | |
| 11 | 5 | |
| 12 | 2 | |
| 13 | 52 | |
| 14 | 14 | |
| 15 | 2 | |
| 16 | 10 | |
| 17 | The Dynamics Of Thin Film Growth: A Modeling Study | 3 |
| 18 | 2 | |
| 19 | 113 | |
| 20 | Restructuring: beware of ripples below surface. | 4 |
About Martha A. Gallivan
Martha A. Gallivan is a scholar working on Statistical and Nonlinear Physics, Condensed Matter Physics and Statistics, Probability and Uncertainty, having authored 25 papers that have together received 383 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (7 papers), Theoretical and Computational Physics (4 papers) and Dendrimers and Hyperbranched Polymers (3 papers). The work is most often cited by research in Polymers and Plastics (95 citations), Computational Mechanics (136 citations) and Statistics, Probability and Uncertainty (17 citations). Martha A. Gallivan has collaborated with scholars based in United States, Türkiye and Mexico. Frequent co-authors include Richard M. Murray, Cihan Oguz, John G. Georgiadis, Richard O. Buckius, David R. Noble, Timothy E. Long, Serkan Ünal, Emel Yılgör, İskender Yılgör and David G. Goodwin. Their work appears in journals such as Journal of Applied Physics, Physical Review B and Macromolecules.
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.