Yae Jee Cho

767 total citations
11 papers, 253 citations indexed

About

Yae Jee Cho is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Yae Jee Cho has authored 11 papers receiving a total of 253 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Electrical and Electronic Engineering, 3 papers in Artificial Intelligence and 2 papers in Molecular Biology. Recurrent topics in Yae Jee Cho's work include Millimeter-Wave Propagation and Modeling (5 papers), Privacy-Preserving Technologies in Data (3 papers) and Advanced MIMO Systems Optimization (3 papers). Yae Jee Cho is often cited by papers focused on Millimeter-Wave Propagation and Modeling (5 papers), Privacy-Preserving Technologies in Data (3 papers) and Advanced MIMO Systems Optimization (3 papers). Yae Jee Cho collaborates with scholars based in South Korea, United States and United Kingdom. Yae Jee Cho's co-authors include Chan‐Byoung Chae, Gauri Joshi, Dimitrios Dimitriadis, Dong Ku Kim, Andre Manoel, Robert B. Sim, Jianyu Wang, Yeon-Geun Lim, Younsun Kim and Min Soo Sim and has published in prestigious journals such as IEEE Communications Magazine, IEEE Wireless Communications and IEEE Journal of Selected Topics in Signal Processing.

In The Last Decade

Yae Jee Cho

11 papers receiving 250 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yae Jee Cho South Korea	7	116	99	62	26	22	11	253
Mastaneh Mokayef Malaysia	7	150 1.3×	87 0.9×	141 2.3×	29 1.1×	14 0.6×	28	271
Jiska Classen Germany	9	162 1.4×	62 0.6×	38 0.6×	80 3.1×	16 0.7×	24	272
Yu Qiao South Korea	10	75 0.6×	77 0.8×	23 0.4×	25 1.0×	24 1.1×	27	195
Nicholas Polosky United States	4	102 0.9×	133 1.3×	62 1.0×	100 3.8×	10 0.5×	5	250
Francesco Devoti Spain	10	201 1.7×	30 0.3×	54 0.9×	72 2.8×	9 0.4×	22	257
Hüseyin Hacı Cyprus	9	263 2.3×	12 0.1×	47 0.8×	65 2.5×	14 0.6×	27	367
Miltiadis C. Filippou Germany	5	154 1.3×	50 0.5×	41 0.7×	102 3.9×	15 0.7×	7	264
Junjie Li China	8	42 0.4×	162 1.6×	15 0.2×	9 0.3×	12 0.5×	28	241
Shaocheng Huang Sweden	7	207 1.8×	101 1.0×	85 1.4×	95 3.7×	6 0.3×	15	295
Tzay-Farn Shih Taiwan	9	110 0.9×	50 0.5×	19 0.3×	167 6.4×	17 0.8×	19	310

Countries citing papers authored by Yae Jee Cho

Since Specialization

Citations

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

Fields of papers citing papers by Yae Jee Cho

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yae Jee Cho. 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 Yae Jee Cho. The network helps show where Yae Jee Cho may publish in the future.

Co-authorship network of co-authors of Yae Jee Cho

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

All Works

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11 of 11 papers shown

Cho, Yae Jee, et al.. (2024). Heterogeneous LoRA for Federated Fine-tuning of On-Device Foundation Models. 12903–12913. 14 indexed citations

Cho, Yae Jee, et al.. (2023). Communication-Efficient and Model-Heterogeneous Personalized Federated Learning via Clustered Knowledge Transfer. IEEE Journal of Selected Topics in Signal Processing. 17(1). 234–247. 39 indexed citations

Cho, Yae Jee, Gauri Joshi, & Dimitrios Dimitriadis. (2023). Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels. 17041–17050. 6 indexed citations

Cho, Yae Jee, et al.. (2022). Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 2881–2887. 58 indexed citations

Lim, Yeon-Geun, Yae Jee Cho, Min Soo Sim, et al.. (2020). Map-Based Millimeter-Wave Channel Models: An Overview, Data for B5G Evaluation and Machine Learning. IEEE Wireless Communications. 27(4). 54–62. 39 indexed citations

Cho, Yae Jee, et al.. (2018). RF Lens-Embedded Antenna Array for mmWave MIMO: Design and Performance. IEEE Communications Magazine. 56(7). 42–48. 58 indexed citations

Lim, Yeon-Geun, et al.. (2018). Relationship Between Cross-Polarization Discrimination (XPD) and Spatial Correlation in Indoor Small-Cell MIMO Systems. IEEE Wireless Communications Letters. 7(4). 654–657. 12 indexed citations

Cho, Yae Jee, Kaibin Huang, & Chan‐Byoung Chae. (2018). V2X Downlink Coverage Analysis with a Realistic Urban Vehicular Model. 55. 1–6. 4 indexed citations

Cho, Yae Jee, H. Birkan Yilmaz, Weisi Guo, & Chan‐Byoung Chae. (2017). Effective Enzyme Deployment for Degradation of Interference Molecules in Molecular Communication. Warwick Research Archive Portal (University of Warwick). 54. 1–6. 13 indexed citations

10.

Lim, Yeon-Geun, Yae Jee Cho, Younsun Kim, & Chan‐Byoung Chae. (2017). Map-based Millimeter-Wave Channel Models: An Overview, Guidelines, and Data.. 5 indexed citations

11.

Cho, Yae Jee, H. Birkan Yilmaz, Weisi Guo, & Chan‐Byoung Chae. (2016). Effective inter‐symbol interference mitigation with a limited amount of enzymes in molecular communications. Transactions on Emerging Telecommunications Technologies. 28(7). 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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