Kailin Tan

612 total citations · 2 hit papers
10 papers, 372 citations indexed

About

Kailin Tan is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, Kailin Tan has authored 10 papers receiving a total of 372 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Electrical and Electronic Engineering, 5 papers in Computer Networks and Communications and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Kailin Tan's work include Error Correcting Code Techniques (5 papers), Advanced Wireless Communication Techniques (5 papers) and Wireless Signal Modulation Classification (3 papers). Kailin Tan is often cited by papers focused on Error Correcting Code Techniques (5 papers), Advanced Wireless Communication Techniques (5 papers) and Wireless Signal Modulation Classification (3 papers). Kailin Tan collaborates with scholars based in China, United States and United Kingdom. Kailin Tan's co-authors include Jincheng Dai, Kai Niu, Sixian Wang, Ping Zhang, Zhongwei Si, Xiaoqi Qin, Ke Yang, Mingzhe Chen, Shuguang Cui and H. Vincent Poor and has published in prestigious journals such as IEEE Journal on Selected Areas in Communications, IEEE Transactions on Cognitive Communications and Networking and GLOBECOM 2022 - 2022 IEEE Global Communications Conference.

In The Last Decade

Kailin Tan

9 papers receiving 368 citations

Hit Papers

Nonlinear Transform Source-Channel Coding for Semantic Co... 2022 2026 2023 2024 2022 2023 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kailin Tan China 5 144 125 120 104 48 10 372
Mikołaj Jankowski United Kingdom 7 202 1.4× 93 0.7× 197 1.6× 104 1.0× 35 0.7× 9 446
Peiwen Jiang China 7 197 1.4× 90 0.7× 181 1.5× 101 1.0× 32 0.7× 16 427
Danlan Huang China 3 181 1.3× 98 0.8× 74 0.6× 78 0.8× 25 0.5× 6 351
Chenghong Bian United Kingdom 8 104 0.7× 93 0.7× 152 1.3× 105 1.0× 42 0.9× 18 321
Shuo Shao China 11 199 1.4× 76 0.6× 131 1.1× 185 1.8× 27 0.6× 46 443
Haider K. Hoomod Iraq 7 107 0.7× 107 0.9× 49 0.4× 64 0.6× 28 0.6× 39 242
Wenhan Zhang United States 9 92 0.6× 111 0.9× 78 0.7× 94 0.9× 41 0.9× 24 297
Bizhu Wang China 8 113 0.8× 52 0.4× 81 0.7× 95 0.9× 29 0.6× 30 270
Yixiang Wang China 11 119 0.8× 57 0.5× 227 1.9× 274 2.6× 46 1.0× 27 458

Countries citing papers authored by Kailin Tan

Since Specialization
Citations

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

Fields of papers citing papers by Kailin Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kailin Tan

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

All Works

10 of 10 papers shown
1.
Wang, Sixian, Jincheng Dai, Kailin Tan, et al.. (2025). DiffCom: Channel Received Signal Is a Natural Condition to Guide Diffusion Posterior Sampling. IEEE Journal on Selected Areas in Communications. 43(7). 2651–2666. 2 indexed citations
2.
Tan, Kailin, Jincheng Dai, Zhenyu Liu, et al.. (2024). Rate-Distortion-Perception Controllable Joint Source-Channel Coding for High-Fidelity Generative Semantic Communications. IEEE Transactions on Cognitive Communications and Networking. 11(2). 672–686. 2 indexed citations
3.
Dai, Jincheng, Sixian Wang, Ke Yang, et al.. (2023). Toward Adaptive Semantic Communications: Efficient Data Transmission via Online Learned Nonlinear Transform Source-Channel Coding. IEEE Journal on Selected Areas in Communications. 41(8). 2609–2627. 25 indexed citations
4.
Tan, Kailin, Jincheng Dai, Sixian Wang, Ke Yang, & Kai Niu. (2023). Learned Image Transmission Toward Machine-Type Semantic Communications. 1–6. 3 indexed citations
5.
Yang, Ke, Sixian Wang, Jincheng Dai, et al.. (2023). WITT: A Wireless Image Transmission Transformer for Semantic Communications. 1–5. 97 indexed citations breakdown →
6.
Dai, Jincheng, Sixian Wang, Kailin Tan, et al.. (2022). Nonlinear Transform Source-Channel Coding for Semantic Communications. IEEE Journal on Selected Areas in Communications. 40(8). 2300–2316. 191 indexed citations breakdown →
7.
Yang, Ke, et al.. (2022). Resolution-Adaptive Source-Channel Coding for End-to-End Wireless Image Transmission. GLOBECOM 2022 - 2022 IEEE Global Communications Conference. 1460–1465. 2 indexed citations
8.
Dai, Jincheng, Kailin Tan, Zhongwei Si, et al.. (2021). Learning to Decode Protograph LDPC Codes. IEEE Journal on Selected Areas in Communications. 39(7). 1983–1999. 45 indexed citations
9.
Zhang, Dexin, Jincheng Dai, Kailin Tan, et al.. (2021). Neural Layered Min-Sum Decoding for Protograph LDPC Codes. 4845–4849.
10.
Niu, Kai, et al.. (2021). Deep Learning Methods for Channel Decoding: A Brief Tutorial. 144–149. 5 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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