Samuel H. Huang

8.7k citations
107 papers · 6.3k indexed · 1 hit paper · h-index 35
Topics
Manufacturing Process and Optimization (29 papers)Product Development and Customization (12 papers)Neural Networks and Applications (11 papers)
Partner nations
United StatesChinaTaiwan

In The Last Decade

Samuel H. Huang

101 papers receiving 5.9k citations

Hit Papers

Additive manufacturing and its societal impact: a literat...201220262016202120124008001.2k

Peers

Samuel H. Huang
Comparison fields: 5 of 183
  • Industrial and Manufacturing Engineering 1.9k
  • Strategy and Management 1.6k
  • Automotive Engineering 1.4k
  • Management Information Systems 1.4k
  • Mechanical Engineering 1.2k
Replace C.K.M. Lee with:
C.K.M. Lee Hong Kong
Ray Y. Zhong Hong Kong
S. Vinodh India
Jan Holmström Finland
Ashutosh Tiwari United Kingdom
Dimitris Mourtzis Greece
Christoph Herrmann Germany
Sami Kara Australia
Konstantinos Salonitis United Kingdom
George Chryssolouris Greece
Samuel H. Huang relative to C.K.M. Lee Hong Kong C.K.M. Lee's profile →
Citations per field
00.5×3.6×
C.K.M. Lee · 1×
Citations per year

Countries citing papers authored by Samuel H. Huang

Since Specialization
Citations

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

Fields of papers citing papers by Samuel H. Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Samuel H. Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Samuel H. Huang. A scholar is included among the top collaborators of Samuel H. Huang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Samuel H. Huang. Samuel H. Huang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 3
3 9
4 30
5 36
6 188
7 2
8 20
9 88
10
Research on Neural Cryptographic Protocols
2
11 22
12 2
13 2
14 96
15 2
16 78
17 136
18 9
19 19
20 62

About Samuel H. Huang

Samuel H. Huang is a scholar working on Industrial and Manufacturing Engineering, Management of Technology and Innovation and Management Information Systems, having authored 107 papers that have together received 6.3k indexed citations. Recurring topics across this work include Manufacturing Process and Optimization (29 papers), Product Development and Customization (12 papers) and Neural Networks and Applications (11 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (1.9k citations), Management Information Systems (1.4k citations) and Automotive Engineering (1.4k citations). Samuel H. Huang has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Liang Hou, Peng Liu, Hongchao Zhang, John P. Dismukes, Tsai‐Chi Kuo, Ranganath Kothamasu, William H. VerDuin, Ge Wang, Mark A. Vonderembse and Huitian Lu. Their work appears in journals such as Macromolecules, Journal of Cleaner Production and Chemical Engineering Journal.

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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