P. Eades

1.4k total citations · 1 hit paper
13 papers, 797 citations indexed

About

P. Eades is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, P. Eades has authored 13 papers receiving a total of 797 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 4 papers in Statistical and Nonlinear Physics and 4 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in P. Eades's work include Data Visualization and Analytics (6 papers), Computational Geometry and Mesh Generation (4 papers) and Complex Network Analysis Techniques (4 papers). P. Eades is often cited by papers focused on Data Visualization and Analytics (6 papers), Computational Geometry and Mesh Generation (4 papers) and Complex Network Analysis Techniques (4 papers). P. Eades collaborates with scholars based in Australia, Canada and Germany. P. Eades's co-authors include Tim Dwyer, Sue Whitesides, Wanchun Li, Seok‐Hee Hong, Seok-Hee Hong, Masahiro Takatsuka, Hui Liu, Xuemin Lin, Weidong Huang and Michael R. Marner and has published in prestigious journals such as Algorithmica, eCite Digital Repository (University of Tasmania) and Medical Entomology and Zoology.

In The Last Decade

P. Eades

12 papers receiving 706 citations

Hit Papers

A Heuristic for Graph Drawing 1984 2026 1998 2012 1984 200 400 600
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.

  1. A Heuristic for Graph Drawing
    1984 660 citations P. Eades profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
P. Eades Australia 6 583 197 155 138 119 13 797
Kazuo Misue Japan 8 512 0.9× 125 0.6× 157 1.0× 127 0.9× 95 0.8× 60 703
David Auber France 15 634 1.1× 265 1.3× 172 1.1× 166 1.2× 53 0.4× 42 857
Shojiro Tagawa Japan 3 403 0.7× 77 0.4× 131 0.8× 129 0.9× 112 0.9× 8 666
Walter Didimo Italy 16 440 0.8× 187 0.9× 94 0.6× 127 0.9× 313 2.6× 95 762
Chris Muelder United States 16 462 0.8× 160 0.8× 142 0.9× 96 0.7× 60 0.5× 23 600
Kai Xu Australia 14 341 0.6× 92 0.5× 101 0.7× 127 0.9× 26 0.2× 65 576
Elizabeth Hetzler United States 8 629 1.1× 108 0.5× 155 1.0× 329 2.4× 31 0.3× 9 848
E. Koutsofios United States 9 257 0.4× 50 0.3× 85 0.5× 209 1.5× 56 0.5× 14 635
S. Havre United States 7 691 1.2× 140 0.7× 194 1.3× 326 2.4× 22 0.2× 13 885
Anushka Anand United States 12 1.0k 1.8× 61 0.3× 296 1.9× 510 3.7× 47 0.4× 16 1.2k

Countries citing papers authored by P. Eades

Since Specialization
Citations

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

Fields of papers citing papers by P. Eades

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of P. Eades

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

All Works

13 of 13 papers shown
1.
Chimani, Markus, P. Eades, Peter Eades, et al.. (2014). People Prefer Less Stress and Fewer Crossings. eCite Digital Repository (University of Tasmania). 2 indexed citations
2.
Liu, Hui, P. Eades, & Seok-Hee Hong. (2012). Visualizing dynamic trajectories in social networks. 2912. 197–204. 3 indexed citations
3.
Li, Wanchun, Seok-Hee Hong, & P. Eades. (2006). A Framework for Visualising Large Graphs. 528–535. 1 indexed citations
4.
Li, Wanchun, P. Eades, & Seok‐Hee Hong. (2005). Navigating Software Architectures with Constant Visual Complexity. 7. 225–232. 8 indexed citations
5.
Eades, P., et al.. (2004). Smooth structural zooming of h-v inclusion tree layouts. 8. 14–25. 5 indexed citations
6.
Dwyer, Tim & P. Eades. (2003). Visualising a fund manager flow graph with columns and worms. 147–152. 35 indexed citations
7.
Eades, P., et al.. (2002). Graph library design. 1190. 144–151.
8.
Eades, P., et al.. (2002). Routing drawings in diagram displays. 11. 291–296. 1 indexed citations
9.
Eades, P., et al.. (1996). Straight-Line Drawing Algorithms for Hierarchical Graphs and Clustered Graphs. 2 indexed citations
10.
Eades, P. & Sue Whitesides. (1996). The Realization Problem for Euclidean Minimum Spanning Trees is NP-Hard. Algorithmica. 16(1). 60–60. 3 indexed citations
11.
Eades, P. & Sue Whitesides. (1996). The realization problem for Euclidean minimum spanning trees is NP-hard. Algorithmica. 16(1). 60–82. 18 indexed citations
12.
Eades, P.. (1984). A Heuristics for Graph Drawing. Medical Entomology and Zoology. 42. 146–160. 59 indexed citations
13.
Eades, P.. (1984). A Heuristic for Graph Drawing. 42. 149–160. 660 indexed citations breakdown →

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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