Joon-Woo Lee

990 total citations · 1 hit paper
30 papers, 510 citations indexed

About

Joon-Woo Lee is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Joon-Woo Lee has authored 30 papers receiving a total of 510 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 9 papers in Computer Networks and Communications. Recurrent topics in Joon-Woo Lee's work include Robotic Path Planning Algorithms (9 papers), Metaheuristic Optimization Algorithms Research (7 papers) and Energy Efficient Wireless Sensor Networks (5 papers). Joon-Woo Lee is often cited by papers focused on Robotic Path Planning Algorithms (9 papers), Metaheuristic Optimization Algorithms Research (7 papers) and Energy Efficient Wireless Sensor Networks (5 papers). Joon-Woo Lee collaborates with scholars based in South Korea, Japan and United States. Joon-Woo Lee's co-authors include Ju-Jang Lee, Byoung-Suk Choi, Young Sik Kim, Jong‐Seon No, Eunsang Lee, Junghyun Lee, Yongwoo Lee, Maxim Deryabin, Jieun Eom and HyungChul Kang and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and IEEE Transactions on Industrial Informatics.

In The Last Decade

Joon-Woo Lee

24 papers receiving 473 citations

Hit Papers

Privacy-Preserving Machine Learning With Fully Homomorphi... 2022 2026 2023 2024 2022 50 100 150
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.

  1. Privacy-Preserving Machine Learning With Fully Homomorphic Encryption for Deep Neural Network
    2022 188 citations Joon-Woo Lee, HyungChul Kang et al. IEEE Access profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Joon-Woo Lee South Korea 11 264 227 131 113 45 30 510
Leili Farzinvash Iran 11 124 0.5× 186 0.8× 115 0.9× 52 0.5× 40 0.9× 36 403
Hongjun Choi South Korea 11 222 0.8× 281 1.2× 98 0.7× 78 0.7× 92 2.0× 50 549
Yasmine Abouelseoud Egypt 10 127 0.5× 111 0.5× 171 1.3× 99 0.9× 83 1.8× 57 447
Peter Langendöerfer Germany 12 248 0.9× 332 1.5× 107 0.8× 83 0.7× 171 3.8× 81 612
Lianming Zhang China 13 152 0.6× 434 1.9× 114 0.9× 56 0.5× 86 1.9× 51 571
Manas Ranjan Kabat India 13 80 0.3× 353 1.6× 108 0.8× 77 0.7× 133 3.0× 55 495
Lukáš Malina Czechia 13 345 1.3× 284 1.3× 180 1.4× 104 0.9× 232 5.2× 86 701
Junwei Liang Singapore 9 171 0.6× 210 0.9× 150 1.1× 42 0.4× 38 0.8× 16 360
Aneta Vulgarakis Feljan Sweden 7 217 0.8× 227 1.0× 210 1.6× 38 0.3× 36 0.8× 13 472

Countries citing papers authored by Joon-Woo Lee

Since Specialization
Citations

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

Fields of papers citing papers by Joon-Woo Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joon-Woo Lee. 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 Joon-Woo Lee. The network helps show where Joon-Woo Lee may publish in the future.

Co-authorship network of co-authors of Joon-Woo Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Joon-Woo Lee. A scholar is included among the top collaborators of Joon-Woo Lee 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 Joon-Woo Lee. Joon-Woo Lee 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.
Park, Dong-Jin, Eunsang Lee, & Joon-Woo Lee. (2025). Powerformer: Efficient and High-Accuracy Privacy-Preserving Language Model with Homomorphic Encryption. 11090–11111.
2.
Lee, Joon-Woo, et al.. (2025). Real-Time Encrypted Emotion Recognition Using Homomorphic Encryption. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies. 9(4). 1–32.
3.
Lee, Joon-Woo, et al.. (2025). Norm-Based Outlier Filtering and Consensus Aggregation for Robust Federated Learning. IEEE Access. 13. 104926–104936.
4.
Lee, Joon-Woo, Dawid Schellingerhout, Sang‐Wuk Jeong, et al.. (2025). Effects of Combining Traditional East Asian and Conventional Western Medicine on Acute Stroke Outcomes. Journal of the American Heart Association. 14(21). e043784–e043784.
5.
Lee, Joon-Woo, et al.. (2023). Key Reduction in Multi-Key and Threshold Multi-Key Homomorphic Encryptions by Reusing Error. IEEE Access. 11. 50310–50324. 1 indexed citations
6.
Lee, Joon-Woo, HyungChul Kang, Yongwoo Lee, et al.. (2022). Privacy-Preserving Machine Learning With Fully Homomorphic Encryption for Deep Neural Network. IEEE Access. 10. 30039–30054. 188 indexed citations breakdown →
7.
Lee, Eunsang, Joon-Woo Lee, Young Sik Kim, & Jong‐Seon No. (2022). Optimization of Homomorphic Comparison Algorithm on RNS-CKKS Scheme. IEEE Access. 10. 26163–26176. 11 indexed citations
8.
Lee, Joon-Woo, Jae-Won Kim, & Jong‐Seon No. (2018). Improvement of Extended Least Difference Greedy Clique-Cover Algorithm for Index Coding. 818–820. 1 indexed citations
9.
Lee, Joon-Woo & Won Ho Kim. (2015). Design of Randomly Deployed Heterogeneous Wireless Sensor Networks by Algorithms Based on Swarm Intelligence. International Journal of Distributed Sensor Networks. 11(8). 690235–690235. 4 indexed citations
10.
11.
Lee, Joon-Woo, et al.. (2013). Gaussian-distributed Particle Swarm Optimization: A novel Gaussian Particle Swarm Optimization. 1122–1127. 10 indexed citations
12.
Lee, Joon-Woo, et al.. (2012). Temporal Waypoint Revision Method to Solve Path Mismatch Problem of Hierarchical Integrated Path Planning for Mobile Vehicle. Journal of Institute of Control Robotics and Systems. 18(7). 664–668. 1 indexed citations
13.
Lee, Joon-Woo, Byoung-Suk Choi, Kyoung-Taik Park, & Ju-Jang Lee. (2011). Comparison between heterogeneous ant colony optimization algorithm and Genetic Algorithm for global path planning of mobile robot. 881–886. 6 indexed citations
14.
Choi, Byoung-Suk, Joon-Woo Lee, & Ju-Jang Lee. (2010). Target-following Scheme for Mobile Robots Based on the Virtual Sub-goal Points. 13(6). 1929–1938. 4 indexed citations
15.
Lee, Joon-Woo & Ju-Jang Lee. (2010). Novel Ant Colony Optimization algorithm with Path Crossover and heterogeneous ants for path planning. 559–564. 14 indexed citations
16.
17.
Lee, Joon-Woo, et al.. (2009). Improved Ant Colony Optimization algorithm by path crossover for optimal path planning. 1996–2000. 10 indexed citations
18.
Lee, Joon-Woo, et al.. (2008). Improved Ant Colony Optimization algorithm by potential field concept for optimal path planning. 2. 662–667. 13 indexed citations
19.
Kim, Seong-Won, et al.. (2007). The VoiceText Text-to-Speech System for the Blizzard Challenge 2007. 1 indexed citations
20.
Lee, Joon-Woo. (1995). ES*: An expert systems development planner using a constraint and rule-based approach. Expert Systems with Applications. 9(1). 3–14. 20 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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