Roger Pearce

49 papers receiving 533 citations

Peers

Roger Pearce
Comparison fields: 5 of 70
  • Hardware and Architecture 136
  • Computer Vision and Pattern Recognition 260
  • Computer Networks and Communications 245
  • Signal Processing 71
  • Information Systems 146
Replace Gabriela Jacques-Silva with:
Gabriela Jacques-Silva United States
Wentao Han China
Shravan Narayanamurthy United States
Satya Gautam Vadlamudi India
Makoto Onizuka Japan
Simon Kahan United States
Jianlong Zhong Singapore
Pingpeng Yuan China
Chuntao Jiang China
Jinyang Li United States
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Citations per field
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Citations per year

Countries citing papers authored by Roger Pearce

Since Specialization
Citations

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

Fields of papers citing papers by Roger Pearce

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Roger Pearce, 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 Roger Pearce Line = papers co-authored together Roger Pearce links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201457
2 201550
3 200842
4 201740
5 201234
6 201927
7 201325
8 202025
9 201422
10 201620
11 201816
12 201913
13 201613
14 201812
15 201612
16 201911
17 201710
18 20198
19 20188
20 20218

About Roger Pearce

Roger Pearce is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Information Systems, Artificial Intelligence and Hardware and Architecture, having authored 52 papers that have together received 548 indexed citations. Recurring topics across this work include Graph Theory and Algorithms (26 papers), Cloud Computing and Resource Management (15 papers), Parallel Computing and Optimization Techniques (13 papers), Distributed and Parallel Computing Systems (11 papers), Advanced Data Storage Technologies (11 papers), Advanced Graph Neural Networks (11 papers), Caching and Content Delivery (10 papers) and Data Management and Algorithms (8 papers). The work is most often cited by research in Hardware and Architecture (136 citations), Computer Vision and Pattern Recognition (260 citations), Computer Networks and Communications (245 citations), Signal Processing (71 citations) and Information Systems (146 citations). Roger Pearce has collaborated with scholars based in United States, Canada and Japan. Frequent co-authors include Maya Gokhale, Brian Van Essen, Nancy M. Amato, Matei Ripeanu, Sasha Ames, Ivy Peng, Barry Chen, Hyojin Kim, Kofi Boakye and Andy Yoo. Their work appears in journals such as AI Magazine, Computer, IEEE Transactions on Parallel and Distributed Systems, Applied immunohistochemistry & molecular morphology and The International Journal of High Performance Computing Applications.

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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