J.M. Burch

2.5k citations
38 papers · 2.0k · h-index 19

Impact in

Papers in

J.M. Burch

36 papers receiving 1.7k citations

Peers

J.M. Burch
Comparison fields: 5 of 110
  • Computer Vision and Pattern Recognition 657
  • Media Technology 255
  • Atomic and Molecular Physics, and Optics 699
  • Acoustics and Ultrasonics 16
  • Computational Mechanics 352
Replace R. Dändliker with:
R. Dändliker Switzerland
Eusebio Bernabéu Spain
T. Asakura Japan
Toshimitsu Asakura Japan
Fernando Mendoza Santoyo Mexico
Karl A. Stetson United States
Gordon D. Love United Kingdom
Daniel Malacara Mexico
Enbang Li Australia
Lorne Whitehead Canada
J.M. Burch relative to R. Dändliker Switzerland R. Dändliker's profile →
Citations per field
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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 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Introduction to Matrix Methods in Optics
1975355
2 1959297
3 1970246
4 1968200
5 1955138
6 2019125
7 195361
8 201853
9 197553
10 196950
11 196549
12 201742
13 196639
14 196630
15 198226
16 197726
17 196123
18 196722
19 201921
20 196517

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 38 papers that have together received 2.0k indexed citations. Recurring topics across this work include Optical measurement and interference techniques (14 papers), Advanced Measurement and Metrology Techniques (11 papers), Surface Roughness and Optical Measurements (6 papers), Advanced Antenna and Metasurface Technologies (4 papers), Metamaterials and Metasurfaces Applications (4 papers), Antenna Design and Analysis (4 papers), Advanced Optical Sensing Technologies (4 papers) and Optical Coatings and Gratings (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (657 citations), Media Technology (255 citations), Atomic and Molecular Physics, and Optics (699 citations), Acoustics and Ultrasonics (16 citations) and Computational Mechanics (352 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, Malte C. Gather, Jonathon R. Harwell, Ifor D. W. Samuel, D. C. Williams and Rosemarie Wilton. Their work appears in journals such as Nature, Optics & Laser Technology, Optical Engineering, Precision Engineering and Photonics.

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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