Canh V. Pham

405 total citations
20 papers, 218 citations indexed

About

Canh V. Pham is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications and Computational Theory and Mathematics. According to data from OpenAlex, Canh V. Pham has authored 20 papers receiving a total of 218 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Statistical and Nonlinear Physics, 8 papers in Computer Networks and Communications and 8 papers in Computational Theory and Mathematics. Recurrent topics in Canh V. Pham's work include Complex Network Analysis Techniques (11 papers), Complexity and Algorithms in Graphs (8 papers) and Opinion Dynamics and Social Influence (8 papers). Canh V. Pham is often cited by papers focused on Complex Network Analysis Techniques (11 papers), Complexity and Algorithms in Graphs (8 papers) and Opinion Dynamics and Social Influence (8 papers). Canh V. Pham collaborates with scholars based in Vietnam, United States and Czechia. Canh V. Pham's co-authors include Tu N. Nguyen, Nguyễn Long Giang, My T. Thai, Jun Pei, Đặng Thị Thanh Huyền, Hoa D. Nguyen, Václav Snåšel, Duc–Tan Tran, Trung Thanh Nguyen and Uyen Trang Nguyen and has published in prestigious journals such as IEEE Access, Computers & Operations Research and Applied Sciences.

In The Last Decade

Canh V. Pham

16 papers receiving 201 citations

Peers

Canh V. Pham
Zhen Lin China
Zhengyou Xia China
Yuqing Zhu China
Qingyuan Gong China
Suqi Cheng China
Ting Hua United States
Keke Huang Singapore
Liudmila Prokhorenkova Russia
Muntadher Saadoon Malaysia
Yabing Yao China
Zhen Lin China
Canh V. Pham
Citations per year, relative to Canh V. Pham Canh V. Pham (= 1×) peers Zhen Lin

Countries citing papers authored by Canh V. Pham

Since Specialization
Citations

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

Fields of papers citing papers by Canh V. Pham

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Canh V. Pham

This figure shows the co-authorship network connecting the top 25 collaborators of Canh V. Pham. A scholar is included among the top collaborators of Canh V. 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 Canh V. Pham. Canh V. 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.
Nguyen, Uyen Trang, et al.. (2025). A New Heuristic Algorithm for Student-Project Allocation with Lecturer Preferences and Ties. Asia Pacific Journal of Operational Research. 42(5).
2.
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Pham, Canh V., et al.. (2023). Minimizing cost for influencing target groups in social network: A model and algorithmic approach. Computer Communications. 212. 182–197. 4 indexed citations
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Pham, Canh V., et al.. (2023). Improved approximation algorithms for k-submodular maximization under a knapsack constraint. Computers & Operations Research. 161. 106452–106452. 1 indexed citations
6.
Pham, Canh V., et al.. (2022). Maximizing k-submodular functions under budget constraint: applications and streaming algorithms. Journal of Combinatorial Optimization. 44(1). 723–751. 4 indexed citations
7.
Pham, Canh V., et al.. (2022). Submodular Maximization Subject to a Knapsack Constraint Under Noise Models. Asia Pacific Journal of Operational Research. 39(6).
8.
Pham, Canh V., et al.. (2022). Fast Streaming Algorithms for k-Submodular Maximization under a Knapsack Constraint. 1–10. 1 indexed citations
9.
Pham, Canh V., et al.. (2021). Efficient Algorithm for Multiple Benefit Thresholds Problem in Online Social Networks. 1–6. 2 indexed citations
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Pham, Canh V., et al.. (2021). Minimum budget for misinformation detection in online social networks with provable guarantees. Optimization Letters. 16(2). 515–544. 4 indexed citations
12.
Giang, Nguyễn Long, et al.. (2020). Multi-Topic Misinformation Blocking With Budget Constraint on Online Social Networks. IEEE Access. 8. 78879–78889. 94 indexed citations
13.
Pham, Canh V., et al.. (2020). Influence Maximization with Priority in Online Social Networks. Algorithms. 13(8). 183–183. 5 indexed citations
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Pham, Canh V., et al.. (2019). Multiple Topics Misinformation blocking in Online Social Networks. 2 indexed citations
16.
Pham, Canh V., et al.. (2019). Minimum budget for misinformation blocking in online social networks. Journal of Combinatorial Optimization. 38(4). 1101–1127. 25 indexed citations
17.
Pham, Canh V., et al.. (2019). Competitive Influence Maximization within Time and Budget Constraints in Online Social Networks: An Algorithmic Approach. Applied Sciences. 9(11). 2274–2274. 15 indexed citations
18.
Pham, Canh V., et al.. (2018). Maximizing misinformation restriction within time and budget constraints. Journal of Combinatorial Optimization. 35(4). 1202–1240. 25 indexed citations
19.
Pham, Canh V., et al.. (2017). Limiting the Spread of Epidemics within Time Constraint on Online Social Networks. 262–269. 18 indexed citations
20.

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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