Wonjong Rhee

4.8k total citations · 3 hit papers
57 papers, 3.1k citations indexed

About

Wonjong Rhee is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Wonjong Rhee has authored 57 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Electrical and Electronic Engineering, 16 papers in Artificial Intelligence and 14 papers in Computer Networks and Communications. Recurrent topics in Wonjong Rhee's work include Cooperative Communication and Network Coding (9 papers), Advanced MIMO Systems Optimization (9 papers) and Advanced Wireless Network Optimization (8 papers). Wonjong Rhee is often cited by papers focused on Cooperative Communication and Network Coding (9 papers), Advanced MIMO Systems Optimization (9 papers) and Advanced Wireless Network Optimization (8 papers). Wonjong Rhee collaborates with scholars based in South Korea, United States and Canada. Wonjong Rhee's co-authors include J.M. Cioffi, Stephen Boyd, Wei Yu, Nihar Jindal, Syed A. Jafar, Andrea Goldsmith, Sriram Vishwanath, Jeongyun Han, Kyung‐Eun Lee and Wei Yu and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Information Theory and Applied Energy.

In The Last Decade

Wonjong Rhee

53 papers receiving 3.0k citations

Hit Papers

Increase in capacity of multiuser OFDM system using dynam... 2002 2026 2010 2018 2002 2004 2005 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wonjong Rhee South Korea 21 2.4k 1.7k 250 166 161 57 3.1k
Panagiotis Demestichas Greece 23 1.7k 0.7× 1.9k 1.1× 244 1.0× 299 1.8× 336 2.1× 232 3.3k
Elhadi Shakshuki Canada 25 788 0.3× 1.4k 0.8× 88 0.4× 379 2.3× 89 0.6× 209 2.4k
Yu Xiao Finland 26 1.1k 0.4× 1.3k 0.8× 177 0.7× 364 2.2× 168 1.0× 150 2.7k
Muhammad Awais Javed Pakistan 24 1.8k 0.7× 1.4k 0.8× 115 0.5× 381 2.3× 326 2.0× 140 2.8k
Teruo Higashino Japan 23 870 0.4× 1.3k 0.7× 177 0.7× 391 2.4× 101 0.6× 262 2.6k
Damla Turgut United States 27 1.3k 0.5× 2.8k 1.6× 255 1.0× 209 1.3× 242 1.5× 145 3.7k
Juan Contreras‐Castillo Mexico 13 803 0.3× 631 0.4× 335 1.3× 245 1.5× 57 0.4× 25 1.8k
Dirk Pesch Ireland 28 2.0k 0.8× 1.7k 1.0× 112 0.4× 207 1.2× 246 1.5× 190 3.0k
Nalini Venkatasubramanian United States 28 930 0.4× 2.2k 1.3× 68 0.3× 451 2.7× 68 0.4× 252 3.3k
Hojung Cha South Korea 30 2.4k 1.0× 1.6k 0.9× 140 0.6× 242 1.5× 300 1.9× 180 3.7k

Countries citing papers authored by Wonjong Rhee

Since Specialization
Citations

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

Fields of papers citing papers by Wonjong Rhee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wonjong Rhee

This figure shows the co-authorship network connecting the top 25 collaborators of Wonjong Rhee. A scholar is included among the top collaborators of Wonjong Rhee 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 Wonjong Rhee. Wonjong Rhee 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.
Lee, Kyung‐Eun, et al.. (2024). Towards a rigorous analysis of mutual information in contrastive learning. Neural Networks. 179. 106584–106584. 2 indexed citations
2.
Kwon, Soonil, et al.. (2024). Visual interpretation of deep learning model in ECG classification: A comprehensive evaluation of feature attribution methods. Computers in Biology and Medicine. 182. 109088–109088.
3.
Lee, Wonseok, et al.. (2024). An Image Grid Can Be Worth a Video: Zero-Shot Video Question Answering Using a VLM. IEEE Access. 12. 193057–193075. 6 indexed citations
4.
Lee, Eunjung, et al.. (2023). AID-purifier: A light auxiliary network for boosting adversarial defense. Neurocomputing. 541. 126251–126251. 5 indexed citations
5.
Kwon, Soonil, Eunjung Lee, Hyo‐Jeong Ahn, et al.. (2023). Machine Learning Prediction for the Recurrence After Electrical Cardioversion of Patients With Persistent Atrial Fibrillation. Korean Circulation Journal. 53(10). 677–677. 6 indexed citations
6.
Rhee, Wonjong, et al.. (2023). An effective low-rank compression with a joint rank selection followed by a compression-friendly training. Neural Networks. 161. 165–177. 13 indexed citations
7.
Rhee, Wonjong, et al.. (2022). Semi-Siamese Bi-encoder Neural Ranking Model Using Lightweight Fine-Tuning. Proceedings of the ACM Web Conference 2022. 502–511. 4 indexed citations
8.
Suh, Jangwon, Eunjung Lee, Jungwon Park, et al.. (2021). Learning ECG Representations for Multi-Label Classification of Cardiac Abnormalities. 1–4. 10 indexed citations
9.
Lee, Eunjung & Wonjong Rhee. (2021). Individualized Short-Term Electric Load Forecasting With Deep Neural Network Based Transfer Learning and Meta Learning. IEEE Access. 9. 15413–15425. 36 indexed citations
10.
Han, Jeongyun, et al.. (2020). Learning analytics dashboards for adaptive support in face-to-face collaborative argumentation. Computers & Education. 163. 104041–104041. 83 indexed citations
11.
Jung, Wonkyung, et al.. (2019). Restructuring Batch Normalization to Accelerate CNN Training.. 1. 14–26. 15 indexed citations
12.
Lee, Kyung‐Eun & Wonjong Rhee. (2019). Graph Convolutional Modules for Traffic Forecasting.. arXiv (Cornell University). 4 indexed citations
13.
Lee, Eunjung, et al.. (2019). Defining virtual control group to improve customer baseline load calculation of residential demand response. Applied Energy. 250. 946–958. 20 indexed citations
14.
Lee, Eunjung, et al.. (2019). The ENERTALK dataset, 15 Hz electricity consumption data from 22 houses in Korea. Scientific Data. 6(1). 193–193. 67 indexed citations
15.
Lee, Hyoseop, et al.. (2019). Data Requirements for Applying Machine Learning to Energy Disaggregation. Energies. 12(9). 1696–1696. 42 indexed citations
16.
Kim, Seungwook, Daeyoung Choi, Eunjung Lee, & Wonjong Rhee. (2017). Churn prediction of mobile and online casual games using play log data. PLoS ONE. 12(7). e0180735–e0180735. 50 indexed citations
17.
Rhee, Wonjong, et al.. (2014). Application of classification algorithms for analysis of road safety risk factor dependencies. Accident Analysis & Prevention. 75. 1–15. 74 indexed citations
18.
Chen, Ming-Yang, Wonjong Rhee, Mehdi Mohseni, & J.M. Cioffi. (2011). Practical Crosstalk Management for Upstream VDSL Using Dynamic Power Control. 1–5. 2 indexed citations
19.
Jindal, Nihar, et al.. (2005). Sum Power Iterative Water-Filling for Multi-Antenna. 2 indexed citations
20.
Yu, Wei, Wonjong Rhee, Stephen Boyd, & J.M. Cioffi. (2004). Iterative Water-Filling for Gaussian Vector Multiple-Access Channels. IEEE Transactions on Information Theory. 50(1). 145–152. 669 indexed citations breakdown →

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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