Jonathan Beaumont

445 citations
10 papers · 321 · h-index 7

Impact in

Papers in

Jonathan Beaumont

10 papers receiving 316 citations

Peers

Jonathan Beaumont
Comparison fields: 5 of 40
  • Computational Mathematics 18
  • Hardware and Architecture 202
  • Computer Networks and Communications 152
  • Computer Vision and Pattern Recognition 109
  • Mathematical Physics 25
Replace Dong-Hyeon Park with:
Dong-Hyeon Park United States
Oleksandr Zinenko United States
Po-An Tsai United States
Jacques A. Pienaar United States
Mehdi Amini United States
Kartik Hegde United States
Guoyang Chen United States
Size Zheng China
Tyler Smith United States
Naser Sedaghati United States
Jonathan Beaumont relative to Dong-Hyeon Park United States Dong-Hyeon Park's profile →
Citations per field
00.5×2.8×
Dong-Hyeon Park · 1×
Citations per year

Countries citing papers authored by Jonathan Beaumont

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Beaumont

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Jonathan Beaumont, 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 Jonathan Beaumont Line = papers co-authored together Jonathan Beaumont links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 2018190
2
Advances in block based fractal coding of still pictures
199029
3 201527
4 201725
5 202014
6 202014
7 201910
8 20196
9 19943
10 20173

About Jonathan Beaumont

Jonathan Beaumont is a scholar working on Computer Networks and Communications, Hardware and Architecture, Computer Vision and Pattern Recognition, Information Systems and Electrical and Electronic Engineering, having authored 10 papers that have together received 321 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (7 papers), Interconnection Networks and Systems (4 papers), Advanced Data Storage Technologies (4 papers), Graph Theory and Algorithms (2 papers), Cloud Computing and Resource Management (2 papers), Low-power high-performance VLSI design (2 papers), Video Coding and Compression Technologies (1 paper) and Error Correcting Code Techniques (1 paper). The work is most often cited by research in Computational Mathematics (18 citations), Hardware and Architecture (202 citations), Computer Networks and Communications (152 citations), Computer Vision and Pattern Recognition (109 citations) and Mathematical Physics (25 citations). Jonathan Beaumont has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Trevor Mudge, Dong-Hyeon Park, Siying Feng, Hun-Seok Kim, Aporva Amarnath, Ronald Dreslinski, Chaitali Chakrabarti, Subhankar Pal, David Blaauw and Scott Mahlke. Their work appears in journals such as IEEE Journal of Solid-State Circuits, Edinburgh Research Explorer and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.

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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