Van‐Nam Huynh

156 papers receiving 2.1k citations

Peers

Van‐Nam Huynh
Comparison fields: 5 of 139
  • Artificial Intelligence 846
  • Management Science and Operations Research 664
  • Computational Theory and Mathematics 404
  • Information Systems 351
  • Control and Systems Engineering 222
Replace Yi‐Chung Hu with:
Yi‐Chung Hu Taiwan
Yu‐Wang Chen United Kingdom
Chonghui Guo China
Alistair Smith United Kingdom
Raquel Ureña Spain
Xiuwu Liao China
Thomas A. Runkler Germany
Pranab K. Muhuri India
Piero P. Bonissone United States
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Van‐Nam Huynh relative to Yi‐Chung Hu Taiwan Yi‐Chung Hu's profile →
Citations per field
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Citations per year

Countries citing papers authored by Van‐Nam Huynh

Since Specialization
Citations

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

Fields of papers citing papers by Van‐Nam Huynh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Van‐Nam Huynh. 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 Van‐Nam Huynh. The network helps show where Van‐Nam Huynh may publish in the future.

Co-authorship network of co-authors of Van‐Nam Huynh

This figure shows the co-authorship network connecting the top 25 collaborators of Van‐Nam Huynh. A scholar is included among the top collaborators of Van‐Nam Huynh 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 Van‐Nam Huynh. Van‐Nam Huynh 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 7
2 1
3 2
4 0
5 4
6 6
7 2
8 1
9 0
10 6
11 2
12 23
13 0
14 4
15
Integrated Uncertainty in Knowledge Modelling and Decision Making 5th International Symposium, IUKM 2016, Da Nang, Vietnam, November 30- December 2, 2016, Proceedings
1
16 17
17 28
18 2
19 1
20
An alternative extension of the k-means algorithm for clustering categorical data
118

About Van‐Nam Huynh

Van‐Nam Huynh is a scholar working on Management Science and Operations Research, Artificial Intelligence and Signal Processing, having authored 171 papers that have together received 2.2k indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (43 papers), Rough Sets and Fuzzy Logic (20 papers) and Data Management and Algorithms (14 papers). The work is most often cited by research in Management Science and Operations Research (664 citations), Artificial Intelligence (846 citations) and Computational Theory and Mathematics (404 citations). Van‐Nam Huynh has collaborated with scholars based in Japan, Thailand and Vietnam. Frequent co-authors include Yoshiteru Nakamori, Songsak Sriboonchitta, Hong-Bin Yan, Nguyễn Cát Hồ, Duy-Tai Dinh, Tieju Ma, Jessada Karnjana, Jonathan Lawry, Tetsuya Murai and Thepchai Supnithi. Their work appears in journals such as Journal of Applied Physics, Journal of Cleaner Production and Expert Systems with Applications.

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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