G.S. May

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

Impact in

Papers in

G.S. May

90 papers receiving 1.2k citations

Peers

G.S. May
Comparison fields: 5 of 84
  • Industrial and Manufacturing Engineering 331
  • Statistics, Probability and Uncertainty 120
  • Electrical and Electronic Engineering 649
  • Control and Systems Engineering 255
  • Architecture 12
Replace Sang Jeen Hong with:
Sang Jeen Hong South Korea
Stephanie Watts Butler United States
M. Hayes Ireland
Cong Hu China
Lijun Zhou China
Lifen Yuan China
Dong Ni China
Eberhard Manske Germany
Yixiang Chen China
Satadru Dey United States
G.S. May relative to Sang Jeen Hong South Korea Sang Jeen Hong's profile →
Citations per field
00.5×1.5×1.8×
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 1993163
2 199491
3 199190
4 200370
5 201263
6 199447
7 200436
8 199535
9 199732
10 200531
11 200030
12 199629
13 199327
14 200024
15 199723
16 199622
17 199721
18 200018
19 199718
20 200517

About G.S. May

G.S. May is a scholar working on Electrical and Electronic Engineering, Industrial and Manufacturing Engineering, Control and Systems Engineering, Mechanical Engineering and Biomedical Engineering, 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), Neural Networks and Applications (10 papers), Microwave Engineering and Waveguides (10 papers) and Experimental Learning in Engineering (8 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (331 citations), Statistics, Probability and Uncertainty (120 citations), Electrical and Electronic Engineering (649 citations), Control and Systems Engineering (255 citations) and Architecture (12 citations). G.S. May has collaborated with scholars based in United States, South Korea and India. Frequent co-authors include Sang Jeen Hong, Byungwhan Kim, Costas J. Spanos, Seung-Soo Han, Tae Seon Kim, A. Erbil, George E. Ponchak, Wasif Tanveer Khan, John Papapolymerou 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 Robotics and Automation.

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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