Marcus R. Garvie

717 citations
22 papers · 582 indexed · h-index 12

Marcus R. Garvie

20 papers receiving 547 citations

Peers

Marcus R. Garvie
Comparison fields: 5 of 67
  • Modeling and Simulation 164
  • Numerical Analysis 88
  • Public Health, Environmental and Occupational Health 344
  • Computer Networks and Communications 217
  • Genetics 195
Replace J. W.-H. So with:
J. W.-H. So Canada
Roger Lui United States
Shengmao Fu China
G.T. Vickers United Kingdom
Yuzo Hosono Japan
Canrong Tian China
Binxiang Dai China
Maria Carmela Lombardo Italy
Matthieu Alfaro France
Alfonso Ruiz-Herrera Spain
Marcus R. Garvie relative to J. W.-H. So Canada J. W.-H. So's profile →
Citations per field
00.5×1.5×2.1×
J. W.-H. So · 1×
Citations per year

Countries citing papers authored by Marcus R. Garvie

Since Specialization
Citations

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

Fields of papers citing papers by Marcus R. Garvie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marcus R. Garvie. 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 Marcus R. Garvie. The network helps show where Marcus R. Garvie may publish in the future.

Co-authorship network

The 8 scholars most cited alongside Marcus R. Garvie, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Marcus R. Garvie Line = papers co-authored together Marcus R. Garvie links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20231
4 20223
5 20204
6 20179
7 20172
8 201528
9 201430
10 20136
11 201028
12 201022
13 201012
14 201040
15 200915
16 2007244
17 200747
18 20064
19 200518
20 200512

About Marcus R. Garvie

Marcus R. Garvie is a scholar working on Modeling and Simulation, Numerical Analysis and Computer Graphics and Computer-Aided Design, having authored 22 papers that have together received 582 indexed citations. Recurring topics across this work include Mathematical and Theoretical Epidemiology and Ecology Models (10 papers), Mathematical Biology Tumor Growth (8 papers), Differential Equations and Numerical Methods (5 papers), Nonlinear Dynamics and Pattern Formation (5 papers), Computational Geometry and Mesh Generation (3 papers), Advanced Mathematical Modeling in Engineering (3 papers), Cellular Automata and Applications (3 papers) and DNA and Biological Computing (2 papers). The work is most often cited by research in Modeling and Simulation (164 citations), Numerical Analysis (88 citations) and Public Health, Environmental and Occupational Health (344 citations). Marcus R. Garvie has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Cătălin Trenchea, James F. Blowey, John Burkardt, Philip K. Maini, Josef Daniel Ackerman, Astrid N. Schwalb, Jeffrey R. Morgan and Fasma Diele. Their work appears in journals such as Journal of Computational Physics, Limnology and Oceanography and SIAM Journal on Control and Optimization.

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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