H.M. Shang

2.6k citations
141 papers · 2.0k indexed · h-index 21

H.M. Shang

136 papers receiving 1.9k citations

Peers

H.M. Shang
Comparison fields: 5 of 96
  • Surfaces, Coatings and Films 406
  • Computer Vision and Pattern Recognition 765
  • Media Technology 228
  • Mechanics of Materials 625
  • Computational Mechanics 460
Replace Xiaojun Liu with:
Xiaojun Liu China
Michael A. Groeber United States
John R. Tyrer United Kingdom
J. W. Dally United States
Dae Wook Kim United States
K. Ramesh India
Hareesh V. Tippur United States
Zixing Lu China
Shuncong Zhong China
Cemal Basaran United States
H.M. Shang relative to Xiaojun Liu China Xiaojun Liu's profile →
Citations per field
00.5×6.5×
Xiaojun Liu · 1×
Citations per year

Countries citing papers authored by H.M. Shang

Since Specialization
Citations

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

Fields of papers citing papers by H.M. Shang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20241
4 20244
5 20232
6
Optical fiber fringe projector for micro-component
20140
7 20015
8 20002
9 19995
10 19992
11
New method for generating high visibility digital speckle shearing fringe pattern
19991
12 199919
13 19971
14 19962
15 199540
16 199210
17 19911
18 19890
19 19855
20 197615

About H.M. Shang

H.M. Shang is a scholar working on Computer Vision and Pattern Recognition, Mechanics of Materials and Computational Mechanics, having authored 141 papers that have together received 2.0k indexed citations. Recurring topics across this work include Optical measurement and interference techniques (66 papers), Advanced Measurement and Metrology Techniques (35 papers), Surface Roughness and Optical Measurements (25 papers), Metal Forming Simulation Techniques (24 papers), Ultrasonics and Acoustic Wave Propagation (18 papers), Structural Health Monitoring Techniques (15 papers), Mechanical Behavior of Composites (15 papers) and Metallurgy and Material Forming (13 papers). The work is most often cited by research in Surfaces, Coatings and Films (406 citations), Computer Vision and Pattern Recognition (765 citations) and Media Technology (228 citations). H.M. Shang has collaborated with scholars based in Singapore, China and United States. Frequent co-authors include C.J. Tay, Chenggen Quan, Guozhong Cao, Katsunori Takahashi, S.L. Toh, Ying Wang, Steven J. Limmer, Tammy P. Chou, F.S. Chau and K.Y. Lam. Their work appears in journals such as Optics & Laser Technology, Optics and Lasers in Engineering, Journal of Materials Processing Technology, Journal of Engineering Materials and Technology and Optics Communications.

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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