G.S. May

1.7k citations
98 papers · 1.3k · h-index 19

Impact in

Papers in

G.S. May

89 papers receiving 1.3k citations

Peers

G.S. May
Comparison fields: 5 of 84
  • Industrial and Manufacturing Engineering 351
  • Statistics, Probability and Uncertainty 123
  • Electrical and Electronic Engineering 670
  • Control and Systems Engineering 269
  • Architecture 13
Replace Sang Jeen Hong with:
Sang Jeen Hong South Korea
Stephanie Watts Butler United States
Martin J. Hayes Ireland
Jong-Soo Kim South Korea
Cong Hu China
Lijun Zhou China
Dong Ni China
Daming Zhang Australia
Shujuan Wang China
Satadru Dey United States
G.S. May relative to Sang Jeen Hong South Korea Sang Jeen Hong's profile →
Citations per field
00.5×1.7×
Sang Jeen Hong · 1×
Citations per year

Countries citing papers authored by G.S. May

Since Specialization
Citations

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

Fields of papers citing papers by G.S. May

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G.S. May. 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 G.S. May. The network helps show where G.S. May may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 98 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1993166
2 199493
3 199190
4 200377
5 201268
6 199452
7 200438
8 199538
9 200533
10 199732
11 200031
12 199629
13 199329
14 200026
15 199624
16 199723
17 199723
18 200020
19 199719
20 200518

About G.S. May

G.S. May is a scholar working on Industrial and Manufacturing Engineering, Electrical and Electronic Engineering, Control and Systems Engineering, Media Technology and Architecture, having authored 98 papers that have together received 1.3k indexed citations. Recurring topics across this work include Industrial Vision Systems and Defect Detection (23 papers), Semiconductor materials and devices (15 papers), Fault Detection and Control Systems (14 papers), Manufacturing Process and Optimization (12 papers), Plasma Diagnostics and Applications (11 papers), Microwave Engineering and Waveguides (10 papers), Neural Networks and Applications (10 papers) and Experimental Learning in Engineering (8 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (351 citations), Statistics, Probability and Uncertainty (123 citations), Electrical and Electronic Engineering (670 citations), Control and Systems Engineering (269 citations) and Architecture (13 citations). G.S. May has collaborated with scholars based in United States, South Korea and Canada. Frequent co-authors include Sang Jeen Hong, Byungwhan Kim, Costas J. Spanos, Seung-Soo Han, Tae Seon Kim, A. Erbil, George E. Ponchak, John Papapolymerou, Wasif Tanveer Khan and Ilgu Yun. Their work appears in journals such as IEEE Transactions on Semiconductor Manufacturing, IEEE Transactions on Electronics Packaging Manufacturing, Journal of Crystal Growth, IEEE Transactions on Advanced Packaging and IEEE Transactions on Microwave Theory and Techniques.

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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