Tsang-Yi Wang

562 total citations
37 papers, 371 citations indexed

About

Tsang-Yi Wang is a scholar working on Computer Networks and Communications, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Tsang-Yi Wang has authored 37 papers receiving a total of 371 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Computer Networks and Communications, 23 papers in Artificial Intelligence and 14 papers in Electrical and Electronic Engineering. Recurrent topics in Tsang-Yi Wang's work include Distributed Sensor Networks and Detection Algorithms (32 papers), Target Tracking and Data Fusion in Sensor Networks (23 papers) and Energy Efficient Wireless Sensor Networks (9 papers). Tsang-Yi Wang is often cited by papers focused on Distributed Sensor Networks and Detection Algorithms (32 papers), Target Tracking and Data Fusion in Sensor Networks (23 papers) and Energy Efficient Wireless Sensor Networks (9 papers). Tsang-Yi Wang collaborates with scholars based in Taiwan, United States and United Kingdom. Tsang-Yi Wang's co-authors include Jwo-Yuh Wu, Pramod K. Varshney, Yunghsiang S. Han, Li-Yuan Chang, Lajos Hanzo, Robert G. Maunder, Bashir M. Al‐Hashimi, Qi Cheng, Pei‐Yin Chen and Biao Chen and has published in prestigious journals such as IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing and IEEE Communications Surveys & Tutorials.

In The Last Decade

Tsang-Yi Wang

32 papers receiving 355 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tsang-Yi Wang Taiwan 10 315 185 150 60 18 37 371
Lifeng Lai United States 10 284 0.9× 245 1.3× 51 0.3× 23 0.4× 15 0.8× 30 383
S.C. Gupta United States 10 266 0.8× 257 1.4× 44 0.3× 40 0.7× 13 0.7× 54 384
Lei Cao United States 10 304 1.0× 280 1.5× 104 0.7× 10 0.2× 9 0.5× 115 405
G. Mergen United States 11 740 2.3× 503 2.7× 138 0.9× 20 0.3× 22 1.2× 16 775
Jun Heo South Korea 11 336 1.1× 362 2.0× 58 0.4× 29 0.5× 5 0.3× 67 456
Chenghong Bian United Kingdom 8 105 0.3× 152 0.8× 104 0.7× 14 0.2× 13 0.7× 18 321
Hong Wen China 7 189 0.6× 279 1.5× 87 0.6× 23 0.4× 27 1.5× 31 399
Ming Yu United States 12 544 1.7× 328 1.8× 49 0.3× 48 0.8× 15 0.8× 50 632
Fei Liang China 6 183 0.6× 327 1.8× 172 1.1× 13 0.2× 19 1.1× 12 445
Peter M. Athanas United States 8 255 0.8× 169 0.9× 48 0.3× 17 0.3× 7 0.4× 39 559

Countries citing papers authored by Tsang-Yi Wang

Since Specialization
Citations

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

Fields of papers citing papers by Tsang-Yi Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tsang-Yi Wang. 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 Tsang-Yi Wang. The network helps show where Tsang-Yi Wang may publish in the future.

Co-authorship network of co-authors of Tsang-Yi Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Tsang-Yi Wang. A scholar is included among the top collaborators of Tsang-Yi Wang 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 Tsang-Yi Wang. Tsang-Yi Wang 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.
Jing, Yindi, Tsang-Yi Wang, & Xinwei Yu. (2022). Blind Distributed Spectrum Sensing with Binary Local Decisions through the Maximum Energy Indicator. ICC 2022 - IEEE International Conference on Communications. 55. 2120–2125. 2 indexed citations
3.
Wang, Tsang-Yi, et al.. (2019). Survey of Turbo, LDPC, and Polar Decoder ASIC Implementations. IEEE Communications Surveys & Tutorials. 21(3). 2309–2333. 100 indexed citations
4.
Wang, Tsang-Yi, et al.. (2016). Distributed Detection of Dynamic Event Regions in Sensor Networks With a Gibbs Field Distribution and Gaussian Corrupted Measurements. IEEE Transactions on Communications. 64(9). 3932–3945. 7 indexed citations
5.
Wang, Tsang-Yi, et al.. (2014). A sliding window approach for dynamic event-region detection in sensor networks. 2025–2028. 6 indexed citations
6.
Chen, Hao & Tsang-Yi Wang. (2013). Distributed detection with common observations. Scholar Works (Boise State University). 2. 5313–5317.
7.
Wang, Tsang-Yi. (2011). Adaptive UWB Pulse Allocation for Distributed Detection in Sensor Networks. IEEE Transactions on Communications. 59(5). 1357–1367. 2 indexed citations
8.
Chang, Li-Yuan, et al.. (2011). A Low-Cost VLSI Architecture for Robust Distributed Estimation in Wireless Sensor Networks. IEEE Transactions on Circuits and Systems I Regular Papers. 58(6). 1277–1286. 5 indexed citations
9.
Duh, Dyi‐Rong, et al.. (2009). Using a Saturation Counter to Improve the Accuracy of Final Decisions in Wireless Sensor Networks.. International Conference on Wireless Networks. 124–129. 1 indexed citations
10.
Chen, Pei‐Yin, Li-Yuan Chang, & Tsang-Yi Wang. (2009). A Low-Cost VLSI Architecture for Fault-Tolerant Fusion Center in Wireless Sensor Networks. IEEE Transactions on Circuits and Systems I Regular Papers. 57(4). 803–813. 3 indexed citations
11.
12.
Wu, Jwo-Yuh, et al.. (2009). Channel-Aware Decision Fusion With Unknown Local Sensor Detection Probability. IEEE Transactions on Signal Processing. 58(3). 1457–1463. 15 indexed citations
13.
Wang, Tsang-Yi, et al.. (2008). Fault-tolerant decision fusion via collaborative sensor fault detection in wireless sensor networks. IEEE Transactions on Wireless Communications. 7(2). 756–768. 17 indexed citations
14.
Wang, Sen‐Hung, et al.. (2008). A synchronization scheme for OFDM systems using the super-imposed perfect sequences. 54. 1–5. 1 indexed citations
15.
Chen, Po‐Ning, et al.. (2007). Performance Analysis and Code Design for Minimum Hamming Distance Fusion in Wireless Sensor Networks. IEEE Transactions on Information Theory. 53(5). 1716–1734. 18 indexed citations
16.
Wang, Tsang-Yi, Yunghsiang S. Han, Biao Chen, & Pramod K. Varshney. (2006). A combined decision fusion and channel coding scheme for distributed fault-tolerant classification in wireless sensor networks. IEEE Transactions on Wireless Communications. 5(7). 1695–1705. 33 indexed citations
17.
Wang, Tsang-Yi, Yunghsiang S. Han, & Pramod K. Varshney. (2005). Fault-tolerant distributed classification based on non-binary codes in wireless sensor networks. IEEE Communications Letters. 9(9). 808–810. 3 indexed citations
18.
Wang, Tsang-Yi, Yunghsiang S. Han, & Pramod K. Varshney. (2004). A combined decision fusion and channel coding scheme for fault-tolerant classification in wireless sensor networks. 2. ii–1073. 6 indexed citations
19.
Wang, Tsang-Yi, Pramod K. Varshney, & Yunghsiang S. Han. (2003). Distributed fault-tolerant classification fusion using error correcting codes. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5099. 47–47. 4 indexed citations
20.
Wang, Tsang-Yi, Yunghsiang S. Han, & Pramod K. Varshney. (2003). Fault-tolerant classification in multisensor networks using coding theory. 772–779. 3 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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