Wee Peng Tay

4.4k total citations · 1 hit paper
189 papers, 2.8k citations indexed

About

Wee Peng Tay is a scholar working on Artificial Intelligence, Computer Networks and Communications and Electrical and Electronic Engineering. According to data from OpenAlex, Wee Peng Tay has authored 189 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 85 papers in Artificial Intelligence, 66 papers in Computer Networks and Communications and 65 papers in Electrical and Electronic Engineering. Recurrent topics in Wee Peng Tay's work include Distributed Sensor Networks and Detection Algorithms (39 papers), Complex Network Analysis Techniques (38 papers) and Indoor and Outdoor Localization Technologies (34 papers). Wee Peng Tay is often cited by papers focused on Distributed Sensor Networks and Detection Algorithms (39 papers), Complex Network Analysis Techniques (38 papers) and Indoor and Outdoor Localization Technologies (34 papers). Wee Peng Tay collaborates with scholars based in Singapore, China and United States. Wee Peng Tay's co-authors include Wuqiong Luo, Mei Leng, Yonggang Wen, Guoqiang Hu, Tony Q. S. Quek, Jianhua Tang, Moe Z. Win, Feng Ji, John N. Tsitsiklis and John N. Tsitsiklis and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Information Theory and IEEE Transactions on Industrial Electronics.

In The Last Decade

Wee Peng Tay

183 papers receiving 2.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Cloud robotics: architecture, challenges and applications

2012 337 citations Wee Peng Tay et al. profile →

Peers

Wee Peng Tay

CNC

EEE

AI

SNP

CSE

Yanheng Liu China

Michael Rabbat Canada

Amiya Nayak Canada

Alex Olshevsky United States

Gil Zussman United States

Ivan Zelinka Czechia

Mark Coates Canada

Kun Liu China

Dawei Zhao China

Shreyas Sundaram United States

Yanheng Liu China

Wee Peng Tay

758 ×0.7

CNC

899 ×0.9

EEE

527 ×0.6

AI

173 ×0.3

SNP

159 ×0.4

CSE

Citations per year, relative to Wee Peng Tay Wee Peng Tay (= 1×) peers Yanheng Liu

Countries citing papers authored by Wee Peng Tay

Since Specialization

Citations

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

Fields of papers citing papers by Wee Peng Tay

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wee Peng Tay. 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 Wee Peng Tay. The network helps show where Wee Peng Tay may publish in the future.

Co-authorship network of co-authors of Wee Peng Tay

This figure shows the co-authorship network connecting the top 25 collaborators of Wee Peng Tay. A scholar is included among the top collaborators of Wee Peng Tay 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 Wee Peng Tay. Wee Peng Tay 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

1.

Ran, Xiaohong, Wee Peng Tay, & Christopher H. T. Lee. (2025). High-Performance Optimization Model Based on Novel Conditional Value At Risk Metric for Power Grids With High Wind Power Penetration. IEEE Transactions on Industrial Informatics. 21(7). 5689–5700. 1 indexed citations

2.

Song, Yang, et al.. (2024). PosDiffNet: Positional Neural Diffusion for Point Cloud Registration in a Large Field of View with Perturbations. Proceedings of the AAAI Conference on Artificial Intelligence. 38(1). 231–239.

3.

Tay, Wee Peng, et al.. (2024). Multi-armed linear bandits with latent biases. Information Sciences. 660. 120103–120103. 2 indexed citations

4.

Ran, Xiaohong, Wee Peng Tay, & Christopher H. T. Lee. (2024). Uncertain Interval-Based Risk Dispatch Approach of Power Systems Under an Unified Framework of Multiple Uncertainties. IEEE Transactions on Industrial Informatics. 21(3). 2053–2063. 2 indexed citations

5.

Ji, Feng, et al.. (2024). Modeling Sparse Graph Sequences and Signals Using Generalized Graphons. IEEE Transactions on Signal Processing. 72. 5048–5064.

6.

Tay, Wee Peng, et al.. (2023). Image Patch-Matching With Graph-Based Learning in Street Scenes. IEEE Transactions on Image Processing. 32. 3465–3480. 6 indexed citations

7.

Yuan, Ye, et al.. (2023). Integrated Transmit Waveform and RIS Phase Shift Design for LPI Detection and Communication. IEEE Transactions on Wireless Communications. 23(6). 5663–5679. 7 indexed citations

8.

Vu, Xuan-Son, et al.. (2022). Reinforced Transformer Learning for VSI-DDoS Detection in Edge Clouds. IEEE Access. 10. 94677–94690. 11 indexed citations

9.

Ji, Feng, et al.. (2022). Signal Processing on Simplicial Complexes With Vertex Signals. IEEE Access. 10. 41889–41901. 4 indexed citations

10.

Tay, Wee Peng, et al.. (2022). Wide-Sense Stationarity in Generalized Graph Signal Processing. IEEE Transactions on Signal Processing. 70. 3414–3428. 4 indexed citations

11.

Ji, Feng, Pratibha Pratibha, & Wee Peng Tay. (2022). Unlimited dynamic range signal recovery for folded graph signals. Signal Processing. 198. 108574–108574. 6 indexed citations

12.

Tay, Wee Peng, et al.. (2021). An Unsupervised Bayesian Neural Network for Truth Discovery in Social Networks. IEEE Transactions on Knowledge and Data Engineering. 34(11). 5182–5195. 9 indexed citations

13.

Song, Yang, et al.. (2019). Compressive Privacy for a Linear Dynamical System. IEEE Transactions on Information Forensics and Security. 15. 895–910. 9 indexed citations

14.

Liu, Xinghua, Wee Peng Tay, Zhi‐Wei Liu, & Gaoxi Xiao. (2019). Quasi-Synchronization of Heterogeneous Networks With a Generalized Markovian Topology and Event-Triggered Communication. IEEE Transactions on Cybernetics. 50(10). 4200–4213. 34 indexed citations

15.

Wang, Junshan, et al.. (2019). Using Social Network Information in Community-Based Bayesian Truth Discovery. IEEE Transactions on Signal and Information Processing over Networks. 5(3). 525–537. 9 indexed citations

16.

Ma, Lijia, Wee Peng Tay, & Gaoxi Xiao. (2018). Iterative expectation maximization for reliable social sensing with information flows. Information Sciences. 501. 621–634. 7 indexed citations

17.

Zhong, Xionghu, et al.. (2018). LaIF: A Lane-Level Self-Positioning Scheme for Vehicles in GNSS-Denied Environments. IEEE Transactions on Intelligent Transportation Systems. 20(8). 2944–2961. 19 indexed citations

18.

Tay, Wee Peng, et al.. (2018). Toward Information Privacy for the Internet of Things: A Nonparametric Learning Approach. IEEE Transactions on Signal Processing. 66(7). 1734–1747. 19 indexed citations

19.

Ji, Feng, et al.. (2018). Estimating Infection Sources in Networks Using Partial Timestamps. IEEE Transactions on Information Forensics and Security. 13(12). 3035–3049. 37 indexed citations

20.

Quitin, François, Philippe De Doncker, François Horlin, & Wee Peng Tay. (2017). Virtual Multiantenna Array for Estimating the Direction of a Transmitter: System, Bounds, and Experimental Results. IEEE Transactions on Vehicular Technology. 67(2). 1510–1520. 10 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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