Minh-Duc Pham
Impact in
-
- Graph Theory and Algorithms
- Signal Processing top 10%
- Data Management and Algorithms
Papers in
-
- Advanced Graph Neural Networks 2
- Semantic Web and Ontologies 2
-
- Graph Theory and Algorithms 3
- Co-authors
- Orri Erling (2 shared papers)Peter Boncz (2 shared papers)Jin‐Soo Lee (3 shared papers)Wook-Shin Han (3 shared papers)Jeffrey Xu Yu (2 shared papers)Alex Averbuch (1 shared paper)Josep-L. Larriba-Pey (1 shared paper)Hassan Chafi (1 shared paper)
- Journals
- Proceedings of the VLDB Endowment (1 paper)Data Archiving and Networked Services (DANS) (2 papers)Open Access System for Information Sharing (Pohang University of Science and Technology) (1 paper)
- Partner nations
- South KoreaNetherlandsHong Kong
In The Last Decade
Minh-Duc Pham
5 papers receiving 238 citations
Peers
Comparison fields: 5 of 39
- Computer Vision and Pattern Recognition 171
- Signal Processing 88
- Computer Networks and Communications 109
- Artificial Intelligence 144
- Information Systems 58
Countries citing papers authored by Minh-Duc Pham
This map shows the geographic impact of Minh-Duc Pham'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 Minh-Duc Pham with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minh-Duc Pham more than expected).
Fields of papers citing papers by Minh-Duc Pham
This network shows the impact of papers produced by Minh-Duc Pham. 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 Minh-Duc Pham. The network helps show where Minh-Duc Pham may publish in the future.
Co-authors
The 11 scholars most cited alongside Minh-Duc Pham, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 135 | |
| 2 | 2010 | 81 | |
| 3 | 2015 | 28 | |
| 4 | 2011 | 7 | |
| 5 | 2010 | 3 |
About Minh-Duc Pham
Minh-Duc Pham is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Computer Networks and Communications and Molecular Biology, having authored 5 papers that have together received 254 indexed citations. Recurring topics across this work include Graph Theory and Algorithms (3 papers), Data Management and Algorithms (2 papers), Advanced Graph Neural Networks (2 papers), Semantic Web and Ontologies (2 papers), Complex Network Analysis Techniques (1 paper), Genomics and Phylogenetic Studies (1 paper), Data Quality and Management (1 paper) and Advanced Database Systems and Queries (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (171 citations), Signal Processing (88 citations), Computer Networks and Communications (109 citations), Artificial Intelligence (144 citations) and Information Systems (58 citations). Minh-Duc Pham has collaborated with scholars based in South Korea, Netherlands and Hong Kong. Frequent co-authors include Orri Erling, Peter Boncz, Jin‐Soo Lee, Wook-Shin Han, Jeffrey Xu Yu, Alex Averbuch, Josep-L. Larriba-Pey, Hassan Chafi, Andrey Gubichev and Hwanjo Yu. Their work appears in journals such as Proceedings of the VLDB Endowment, Data Archiving and Networked Services (DANS) and Open Access System for Information Sharing (Pohang University of Science and Technology).
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.