John Clyne

999 total citations
27 papers, 586 citations indexed

About

John Clyne is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Computer Networks and Communications. According to data from OpenAlex, John Clyne has authored 27 papers receiving a total of 586 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 14 papers in Computer Graphics and Computer-Aided Design and 5 papers in Computer Networks and Communications. Recurrent topics in John Clyne's work include Computer Graphics and Visualization Techniques (14 papers), Image and Signal Denoising Methods (9 papers) and Advanced Data Compression Techniques (7 papers). John Clyne is often cited by papers focused on Computer Graphics and Visualization Techniques (14 papers), Image and Signal Denoising Methods (9 papers) and Advanced Data Compression Techniques (7 papers). John Clyne collaborates with scholars based in United States, Argentina and Germany. John Clyne's co-authors include Mark Rast, Pablo D. Mininni, Alan Norton, Shaomeng Li, Kwan‐Liu Ma, Eric B. Lum, Leigh Orf, Hank Childs, Peter Lindström and Jonathan Woodring and has published in prestigious journals such as Physics of Fluids, New Journal of Physics and IEEE Transactions on Visualization and Computer Graphics.

In The Last Decade

John Clyne

26 papers receiving 556 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John Clyne United States 11 189 161 155 110 99 27 586
Alan Norton United States 10 210 1.1× 91 0.6× 247 1.6× 66 0.6× 209 2.1× 16 671
Shaomeng Li United States 8 139 0.7× 43 0.3× 56 0.4× 36 0.3× 14 0.1× 15 417
Mark Rast United States 17 41 0.2× 655 4.1× 31 0.2× 118 1.1× 161 1.6× 51 897
Terry J. Ligocki United States 13 52 0.3× 43 0.3× 121 0.8× 17 0.2× 306 3.1× 28 641
W. P. Dannevik United States 9 32 0.2× 42 0.3× 42 0.3× 136 1.2× 169 1.7× 22 425
Ross Heikes United States 11 32 0.2× 51 0.3× 53 0.3× 538 4.9× 164 1.7× 14 875
Margarete Oliveira Domingues Brazil 13 45 0.2× 236 1.5× 18 0.1× 100 0.9× 227 2.3× 67 666
Pierre Chainais France 12 113 0.6× 58 0.4× 14 0.1× 15 0.1× 68 0.7× 51 525
Alireza Hadjighasem United States 7 34 0.2× 36 0.2× 19 0.1× 172 1.6× 207 2.1× 9 559
James L. Helman United States 6 335 1.8× 8 0.0× 422 2.7× 43 0.4× 279 2.8× 10 689

Countries citing papers authored by John Clyne

Since Specialization
Citations

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

Fields of papers citing papers by John Clyne

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Clyne

This figure shows the co-authorship network connecting the top 25 collaborators of John Clyne. A scholar is included among the top collaborators of John Clyne 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 John Clyne. John Clyne 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.
Kumar, Bipin, et al.. (2022). Development of NCL equivalent serial and parallel python routines for meteorological data analysis. The International Journal of High Performance Computing Applications. 36(3). 337–355. 2 indexed citations
2.
Clyne, John, et al.. (2021). Using Neural Networks for Two Dimensional Scientific Data Compression. 2021 IEEE International Conference on Big Data (Big Data). 2956–2965. 6 indexed citations
3.
Li, Shaomeng, et al.. (2019). VAPOR: A Visualization Package Tailored to Analyze Simulation Data in Earth System Science. Atmosphere. 10(9). 488–488. 90 indexed citations
4.
Li, Shaomeng, et al.. (2018). Data Reduction Techniques for Simulation, Visualization and Data Analysis. Computer Graphics Forum. 37(6). 422–447. 50 indexed citations
5.
Gruchalla, Kenny, et al.. (2017). Contextual Compression of Large-Scale Wind Turbine Array Simulations. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 2 indexed citations
6.
Li, Shaomeng, et al.. (2017). Spatiotemporal Wavelet Compression for Visualization of Scientific Simulation Data. 45. 216–227. 9 indexed citations
7.
Li, Shaomeng, et al.. (2017). Achieving Portable Performance For Wavelet Compression Using Data Parallel Primitives. Eurographics. 9 indexed citations
8.
Röber, Niklas, et al.. (2016). Icosahedral Maps for a Multiresolution Representation of Earth Data. Eurographics. 161–168. 3 indexed citations
9.
Clyne, John, et al.. (2015). Multiresolution visualization of digital earth data via hexagonal box-spline wavelets. 8. 151–152. 1 indexed citations
10.
Li, Shaomeng, Kenny Gruchalla, Kristin Potter, John Clyne, & Hank Childs. (2015). Evaluating the efficacy of wavelet configurations on turbulent-flow data. 81–89. 14 indexed citations
11.
Norton, Alan & John Clyne. (2013). Interactive analysis and visualization of massive earth system models using VAPOR. EGU General Assembly Conference Abstracts. 13113. 1 indexed citations
12.
Clyne, John & Alan Norton. (2013). An intelligent data model for the storage of structured grids. EGUGA. 13082. 1 indexed citations
13.
Clyne, John, Pablo D. Mininni, & A. J. Norton. (2012). Physically-Based Feature Tracking for CFD Data. IEEE Transactions on Visualization and Computer Graphics. 19(6). 1020–1033. 10 indexed citations
14.
Norton, Alan & John Clyne. (2012). The VAPOR Visualization Application.. 5 indexed citations
15.
Gruchalla, Kenny, Mark Rast, Elizabeth Bradley, John Clyne, & Pablo D. Mininni. (2009). Visualization-driven Structural and Statistical Analysis of Turbulent Flows. Lecture notes in computer science. 5772. 321.
16.
Mininni, Pablo D., Ed Lee, Alan Norton, & John Clyne. (2008). Flow visualization and field line advection in computational fluid dynamics: application to magnetic fields and turbulent flows. New Journal of Physics. 10(12). 125007–125007. 14 indexed citations
17.
Joy, Kenneth I., Mark Carl Miller, Hank Childs, et al.. (2007). Frameworks for visualization at the extreme scale. Journal of Physics Conference Series. 78. 12035–12035. 2 indexed citations
18.
Clyne, John, Pablo D. Mininni, Alan Norton, & Mark Rast. (2007). Interactive desktop analysis of high resolution simulations: application to turbulent plume dynamics and current sheet formation. New Journal of Physics. 9(8). 301–301. 176 indexed citations
19.
Lum, Eric B., Kwan‐Liu Ma, & John Clyne. (2002). A hardware-assisted scalable solution for interactive volume rendering of time-varying data. IEEE Transactions on Visualization and Computer Graphics. 8(3). 286–301. 43 indexed citations
20.
Lum, Eric B., Kwan‐Liu Ma, & John Clyne. (2001). Texture hardware assisted rendering of time-varying volume data. 263–563. 37 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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