J.M. Burch

2.5k citations
37 papers · 1.7k · h-index 19

Impact in

Papers in

J.M. Burch

35 papers receiving 1.5k citations

Peers

J.M. Burch
Comparison fields: 5 of 110
  • Computer Vision and Pattern Recognition 562
  • Media Technology 222
  • Atomic and Molecular Physics, and Optics 617
  • Acoustics and Ultrasonics 15
  • Computational Mechanics 312
Replace R. Dändliker with:
R. Dändliker Switzerland
A.E. Ennos United Kingdom
Eusebio Bernabéu Spain
Lawrence B. Wolff United States
T. Asakura Japan
Enbang Li Australia
Anbo Wang United States
Gordon D. Love United Kingdom
Karl A. Stetson United States
Alyosha Molnar United States
J.M. Burch relative to R. Dändliker Switzerland R. Dändliker's profile →
Citations per field
00.5×1.5×
R. Dändliker · 1×
Citations per year

Countries citing papers authored by J.M. Burch

Since Specialization
Citations

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

Fields of papers citing papers by J.M. Burch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J.M. Burch. 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 J.M. Burch. The network helps show where J.M. Burch may publish in the future.

Co-authors

The 24 scholars most cited alongside J.M. Burch, 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 J.M. Burch Line = papers co-authored together J.M. Burch links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Introduction to Matrix Methods in Optics
1975330
2 1959251
3 1970211
4 1968179
5 1955125
6 2019119
7 201852
8 195351
9 196943
10 197542
11 201740
12 196536
13 196633
14 196623
15 197722
16 201921
17 198221
18 196719
19 196118
20 196514

About J.M. Burch

J.M. Burch is a scholar working on Computer Vision and Pattern Recognition, Mechanical Engineering, Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics and Computational Mechanics, having authored 37 papers that have together received 1.7k indexed citations. Recurring topics across this work include Optical measurement and interference techniques (13 papers), Advanced Measurement and Metrology Techniques (10 papers), Surface Roughness and Optical Measurements (6 papers), Antenna Design and Analysis (4 papers), Advanced Antenna and Metasurface Technologies (4 papers), Metamaterials and Metasurfaces Applications (4 papers), Advanced Optical Sensing Technologies (4 papers) and Ocular and Laser Science Research (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (562 citations), Media Technology (222 citations), Atomic and Molecular Physics, and Optics (617 citations), Acoustics and Ultrasonics (15 citations) and Computational Mechanics (312 citations). J.M. Burch has collaborated with scholars based in United Kingdom, United States and Netherlands. Frequent co-authors include Walter Stiles, A.E. Ennos, E. Archbold, Andrea Di Falco, C. Forno, Jonathon R. Harwell, Ifor D. W. Samuel, Malte C. Gather, D. C. Williams and Rosemarie Wilton. Their work appears in journals such as Nature, Optics & Laser Technology, Precision Engineering, Optical Engineering and Scientific Reports.

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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