Pei-Duo Yu

440 total citations
20 papers, 222 citations indexed

About

Pei-Duo Yu is a scholar working on Statistical and Nonlinear Physics, Information Systems and Artificial Intelligence. According to data from OpenAlex, Pei-Duo Yu has authored 20 papers receiving a total of 222 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Statistical and Nonlinear Physics, 7 papers in Information Systems and 5 papers in Artificial Intelligence. Recurrent topics in Pei-Duo Yu's work include Complex Network Analysis Techniques (7 papers), Opinion Dynamics and Social Influence (4 papers) and Data-Driven Disease Surveillance (4 papers). Pei-Duo Yu is often cited by papers focused on Complex Network Analysis Techniques (7 papers), Opinion Dynamics and Social Influence (4 papers) and Data-Driven Disease Surveillance (4 papers). Pei-Duo Yu collaborates with scholars based in Taiwan, Singapore and Hong Kong. Pei-Duo Yu's co-authors include Chee Wei Tan, Ching Nam Hang, Hung‐Lin Fu, Michael Fuchs, Roberto Morabito, Wenyi Zhang, Jiasi Chen, Guanrong Chen, H. Vincent Poor and M.F. Wong and has published in prestigious journals such as IEEE Transactions on Signal Processing, IEEE Access and IEEE Journal of Selected Topics in Signal Processing.

In The Last Decade

Pei-Duo Yu

19 papers receiving 218 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Pei-Duo Yu Taiwan	10	74	50	48	45	33	20	222
Amulya Yadav United States	10	52 0.7×	67 1.3×	36 0.8×	39 0.9×	33 1.0×	35	229
Valerio La Gatta Italy	7	103 1.4×	12 0.2×	16 0.3×	33 0.7×	27 0.8×	19	206
Sumio Fujita Japan	10	135 1.8×	33 0.7×	20 0.4×	118 2.6×	24 0.7×	53	269
Qamar Rayees Khan India	9	218 2.9×	14 0.3×	68 1.4×	67 1.5×	29 0.9×	17	411
Syed Tanzeel Rabani India	9	230 3.1×	14 0.3×	76 1.6×	69 1.5×	20 0.6×	16	416
Akib Mohi Ud Din Khanday India	10	234 3.2×	14 0.3×	76 1.6×	68 1.5×	19 0.6×	23	441
Abdulaziz Alashaikh Saudi Arabia	8	91 1.2×	9 0.2×	33 0.7×	41 0.9×	108 3.3×	18	305
Nan Han China	10	63 0.9×	59 1.2×	34 0.7×	50 1.1×	40 1.2×	25	295
Avaré Stewart Germany	9	64 0.9×	34 0.7×	56 1.2×	46 1.0×	17 0.5×	22	178
Mohamad Farhan Mohamad Mohsin Malaysia	10	62 0.8×	17 0.3×	12 0.3×	80 1.8×	29 0.9×	47	290

Countries citing papers authored by Pei-Duo Yu

Since Specialization

Citations

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

Fields of papers citing papers by Pei-Duo Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pei-Duo Yu. 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 Pei-Duo Yu. The network helps show where Pei-Duo Yu may publish in the future.

Co-authorship network of co-authors of Pei-Duo Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Pei-Duo Yu. A scholar is included among the top collaborators of Pei-Duo Yu 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 Pei-Duo Yu. Pei-Duo Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Tan, Chee Wei, et al.. (2025). DeepTrace: Learning to Optimize Contact Tracing in Epidemic Networks With Graph Neural Networks. IEEE Transactions on Signal and Information Processing over Networks. 11. 97–113. 4 indexed citations

Yu, Pei-Duo & Chee Wei Tan. (2025). Unraveling the Viral Spread of Misinformation: Maximum-Likelihood Estimation and Starlike Tree Approximation in Markovian Spreading Models. IEEE Transactions on Signal Processing. 73. 446–461.

Hang, Ching Nam, Pei-Duo Yu, & Chee Wei Tan. (2025). TrumorGPT: Graph-Based Retrieval-Augmented Large Language Model for Fact-Checking. IEEE Transactions on Artificial Intelligence. 6(11). 3148–3162. 8 indexed citations

Hang, Ching Nam, Pei-Duo Yu, & Chee Wei Tan. (2024). TrumorGPT: Query Optimization and Semantic Reasoning over Networks for Automated Fact-Checking. 1–6. 11 indexed citations

Hang, Ching Nam, Pei-Duo Yu, Roberto Morabito, & Chee Wei Tan. (2024). Large Language Models Meet Next-Generation Networking Technologies: A Review. Future Internet. 16(10). 365–365. 22 indexed citations

Hang, Ching Nam, Chee Wei Tan, & Pei-Duo Yu. (2024). MCQGen: A Large Language Model-Driven MCQ Generator for Personalized Learning. IEEE Access. 12. 102261–102273. 37 indexed citations

Yu, Pei-Duo, Zheng Liang, & Chee Wei Tan. (2024). Contagion Source Detection by Maximum Likelihood Estimation and Starlike Graph Approximation. 1–6. 2 indexed citations

Tan, Chee Wei & Pei-Duo Yu. (2023). Contagion Source Detection in Epidemic and Infodemic Outbreaks: Mathematical Analysis and Network Algorithms. arXiv (Cornell University). 13(2-3). 107–251. 10 indexed citations

Hang, Ching Nam, et al.. (2023). Privacy-Enhancing Digital Contact Tracing with Machine Learning for Pandemic Response: A Comprehensive Review. Big Data and Cognitive Computing. 7(2). 108–108. 13 indexed citations

10.

Hang, Ching Nam, et al.. (2023). MEGA: Machine Learning-Enhanced Graph Analytics for Infodemic Risk Management. IEEE Journal of Biomedical and Health Informatics. 27(12). 6100–6111. 14 indexed citations

11.

Yu, Pei-Duo, Chee Wei Tan, & Hung‐Lin Fu. (2022). Epidemic Source Detection in Contact Tracing Networks: Epidemic Centrality in Graphs and Message-Passing Algorithms. IEEE Journal of Selected Topics in Signal Processing. 16(2). 234–249. 19 indexed citations

12.

Yu, Pei-Duo, et al.. (2022). Identifying the Superspreader in Proactive Backward Contact Tracing by Deep Learning. 43–48. 4 indexed citations

13.

Tan, Chee Wei, et al.. (2020). Mathematics Gamification in Mobile App Software for Personalized Learning at Scale. 1–5. 6 indexed citations

14.

Hang, Ching Nam, et al.. (2018). Parallel Counting of Triangles in Large Graphs: Pruning and Hierarchical Clustering Algorithms. 36. 1–6. 2 indexed citations

15.

Yu, Pei-Duo, Chee Wei Tan, & Hung‐Lin Fu. (2018). Averting Cascading Failures in Networked Infrastructures: Poset-Constrained Graph Algorithms. IEEE Journal of Selected Topics in Signal Processing. 12(4). 733–748. 16 indexed citations

16.

Tan, Chee Wei, et al.. (2017). Teaching Computational Thinking by Gamification of K-12 Mathematics: Mobile App Math Games in Mathematics and Computer Science Tournament. 55–59. 5 indexed citations

17.

Yu, Pei-Duo, Chee Wei Tan, & Hung‐Lin Fu. (2017). Rumor Source Detection in Finite Graphs with Boundary Effects by Message-passing Algorithms. 86–90. 7 indexed citations

18.

Yu, Pei-Duo, Chee Wei Tan, & Hung‐Lin Fu. (2017). Rumor source detection in unicyclic graphs. 439–443. 7 indexed citations

19.

Tan, Chee Wei, et al.. (2016). Optimal detection of influential spreaders in online social networks. 145–150. 16 indexed citations

20.

Fuchs, Michael & Pei-Duo Yu. (2015). Rumor source detection for rumor spreading on random increasing trees. Electronic Communications in Probability. 20(none). 19 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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