James Saunderson

629 total citations
32 papers, 281 citations indexed

About

James Saunderson is a scholar working on Computational Mechanics, Numerical Analysis and Computational Theory and Mathematics. According to data from OpenAlex, James Saunderson has authored 32 papers receiving a total of 281 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computational Mechanics, 10 papers in Numerical Analysis and 10 papers in Computational Theory and Mathematics. Recurrent topics in James Saunderson's work include Sparse and Compressive Sensing Techniques (11 papers), Advanced Optimization Algorithms Research (10 papers) and Blind Source Separation Techniques (3 papers). James Saunderson is often cited by papers focused on Sparse and Compressive Sensing Techniques (11 papers), Advanced Optimization Algorithms Research (10 papers) and Blind Source Separation Techniques (3 papers). James Saunderson collaborates with scholars based in Australia, United States and United Kingdom. James Saunderson's co-authors include Pablo A. Parrilo, Hamza Fawzi, Alan S. Willsky, Anthony Wirth, Emanuele Viterbo, Matthew R. Johnson, Sajjad Hadavi, Behrooz Bahrani, Ali Mehrizi‐Sani and Mario Boley and has published in prestigious journals such as IEEE Transactions on Information Theory, IEEE Transactions on Power Systems and Computer Physics Communications.

In The Last Decade

James Saunderson

30 papers receiving 268 citations

Peers

James Saunderson
Comparison fields: 5 of 61
  • Artificial Intelligence 108
  • Computational Theory and Mathematics 60
  • Computer Vision and Pattern Recognition 54
  • Electrical and Electronic Engineering 40
  • Control and Systems Engineering 37
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Citations per field, relative to James Saunderson
James Saunderson · 1×
Citations per year, relative to James Saunderson
James Saunderson · 1×

Countries citing papers authored by James Saunderson

Since Specialization
Citations

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

Fields of papers citing papers by James Saunderson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Saunderson

This figure shows the co-authorship network connecting the top 25 collaborators of James Saunderson. A scholar is included among the top collaborators of James Saunderson 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 James Saunderson. James Saunderson 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
# Work Indexed citations
1 3
2 1
3 2
4 1
5 1
6 18
7 7
8 9
9 18
10 1
11 6
12 53
13 2
14 4
15 26
16
Analyzing Hogwild Parallel Gaussian Gibbs Sampling
23
17 1
18 1
19 40
20
Mostow's Rigidity Theorem
1

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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