Phu Pham

560 total citations
27 papers, 335 citations indexed

About

Phu Pham is a scholar working on Artificial Intelligence, Information Systems and Statistical and Nonlinear Physics. According to data from OpenAlex, Phu Pham has authored 27 papers receiving a total of 335 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 12 papers in Information Systems and 10 papers in Statistical and Nonlinear Physics. Recurrent topics in Phu Pham's work include Advanced Graph Neural Networks (17 papers), Complex Network Analysis Techniques (10 papers) and Recommender Systems and Techniques (10 papers). Phu Pham is often cited by papers focused on Advanced Graph Neural Networks (17 papers), Complex Network Analysis Techniques (10 papers) and Recommender Systems and Techniques (10 papers). Phu Pham collaborates with scholars based in Vietnam, Poland and United States. Phu Pham's co-authors include Phuc Do, Bay Vo, Loan T. T. Nguyen, Unil Yun, Jiebo Luo, Róbert Kozma, Witold Pedrycz, Ngoc Thanh Nguyên, Mark W. J. van Passel and Jerry Chun‐Wei Lin and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, Expert Systems with Applications and Frontiers in Microbiology.

In The Last Decade

Phu Pham

25 papers receiving 324 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Phu Pham Vietnam 9 175 107 61 40 37 27 335
Shuiqiao Yang Australia 12 326 1.9× 91 0.9× 51 0.8× 89 2.2× 15 0.4× 26 496
Blake Shaw United States 8 141 0.8× 44 0.4× 92 1.5× 37 0.9× 33 0.9× 16 400
Loulwah AlSumait Kuwait 4 204 1.2× 116 1.1× 106 1.7× 90 2.3× 55 1.5× 6 410
Pengsheng Ji United States 6 100 0.6× 32 0.3× 89 1.5× 11 0.3× 36 1.0× 11 281
Sumio Fujita Japan 10 135 0.8× 118 1.1× 33 0.5× 20 0.5× 7 0.2× 53 269
Furqan Aziz United Kingdom 10 178 1.0× 32 0.3× 96 1.6× 40 1.0× 7 0.2× 29 382
Tsai-Ching Lu United States 10 167 1.0× 44 0.4× 74 1.2× 49 1.2× 6 0.2× 36 304
Qamar Rayees Khan India 9 218 1.2× 67 0.6× 14 0.2× 68 1.7× 27 0.7× 17 411
Akib Mohi Ud Din Khanday India 10 234 1.3× 68 0.6× 14 0.2× 76 1.9× 27 0.7× 23 441
Syed Tanzeel Rabani India 9 230 1.3× 69 0.6× 14 0.2× 76 1.9× 27 0.7× 16 416

Countries citing papers authored by Phu Pham

Since Specialization
Citations

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

Fields of papers citing papers by Phu Pham

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Phu 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 Phu Pham. The network helps show where Phu Pham may publish in the future.

Co-authorship network of co-authors of Phu Pham

This figure shows the co-authorship network connecting the top 25 collaborators of Phu Pham. A scholar is included among the top collaborators of Phu Pham 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 Phu Pham. Phu Pham 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
1.
Pham, Phu, et al.. (2025). Topological Data Analysis in Graph Neural Networks: Surveys and Perspectives. IEEE Transactions on Neural Networks and Learning Systems. 36(6). 9758–9776. 6 indexed citations
2.
3.
Pham, Phu. (2024). An integrated simplicial neural network with neuro-fuzzy network for graph embedding. International Journal of Machine Learning and Cybernetics. 16(1). 233–251. 4 indexed citations
4.
Pham, Phu. (2024). A Structure-Enhanced Heterogeneous Graph Representation Learning with Attention-Supplemented Embedding Fusion. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems. 32(3). 325–354.
5.
Pham, Phu, et al.. (2023). Enhancing Anchor Link Prediction in Information Networks through Integrated Embedding Techniques. Information Sciences. 645. 119331–119331. 7 indexed citations
6.
Pham, Phu, Thanh Tuan Nguyen, Zhisheng Zhang, et al.. (2023). Comparative Transcriptome Analysis and Expression of Genes Associated with Polysaccharide Biosynthesis in Dendrobium officinale Diploid and Tetraploid Plants. Agronomy. 14(1). 69–69. 2 indexed citations
7.
Pham, Phu, Loan T. T. Nguyen, Ngoc Thanh Nguyên, et al.. (2023). An Approach to Semantic-Aware Heterogeneous Network Embedding for Recommender Systems. IEEE Transactions on Cybernetics. 53(9). 6027–6040. 18 indexed citations
8.
Mõttus, Matti, et al.. (2022). TAIGA: A Novel Dataset for Multitask Learning of Continuous and Categorical Forest Variables From Hyperspectral Imagery. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–11. 9 indexed citations
9.
Pham, Phu, Witold Pedrycz, & Bay Vo. (2022). Dual attention-based sequential auto-encoder for Covid-19 outbreak forecasting: A case study in Vietnam. Expert Systems with Applications. 203. 117514–117514. 8 indexed citations
10.
Do, Phuc & Phu Pham. (2022). Heterogeneous graph convolutional network pre-training as side information for improving recommendation. Neural Computing and Applications. 34(18). 15945–15961. 8 indexed citations
11.
Pham, Phu, et al.. (2021). Automatic topic labelling for text document using ontology of graph-based concepts and dependency graph. International Journal of Business Information Systems. 36(2). 221–221. 1 indexed citations
12.
Pham, Phu, Loan T. T. Nguyen, Ngoc Thanh Nguyên, et al.. (2021). ComGCN: Community-Driven Graph Convolutional Network for Link Prediction in Dynamic Networks. IEEE Transactions on Systems Man and Cybernetics Systems. 52(9). 5481–5493. 26 indexed citations
13.
Pham, Phu, Loan T. T. Nguyen, Bay Vo, & Unil Yun. (2021). Bot2Vec: A general approach of intra-community oriented representation learning for bot detection in different types of social networks. Information Systems. 103. 101771–101771. 45 indexed citations
14.
Do, Phuc & Phu Pham. (2021). W-KG2Vec: a weighted text-enhanced meta-path-based knowledge graph embedding for similarity search. Neural Computing and Applications. 33(23). 16533–16555. 4 indexed citations
15.
Pham, Phu & Phuc Do. (2021). W-MMP2Vec: Topic-driven network embedding model for link prediction in content-based heterogeneous information network. Intelligent Data Analysis. 25(3). 711–738. 4 indexed citations
16.
Pham, Phu & Phuc Do. (2020). W-Com2Vec: A topic-driven meta-path- based intra-community embedding for content-based heterogeneous information network. Intelligent Data Analysis. 24(5). 1207–1233. 3 indexed citations
17.
Pham, Phu & Phuc Do. (2019). W-MetaPath2Vec: The topic-driven meta-path-based model for large-scaled content-based heterogeneous information network representation learning. Expert Systems with Applications. 123. 328–344. 23 indexed citations
18.
Pham, Phu & Phuc Do. (2018). Topic-driven top-k similarity search by applying constrained meta-path based in content-based schema-enriched heterogeneous information network. International Journal of Business Intelligence and Data Mining. 1(1). 1–1. 1 indexed citations
19.
20.
Gonzalez, Teresita d. J. Bello, Phu Pham, Janetta Top, et al.. (2017). Characterization of Enterococcus Isolates Colonizing the Intestinal Tract of Intensive Care Unit Patients Receiving Selective Digestive Decontamination. Frontiers in Microbiology. 8. 1596–1596. 20 indexed citations

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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