Intelligent Network and Convergence Laboratory
We focus on empowering networks to operate more intelligently and
enabling all things to connect and exchange data with each other seamlessly,
learn from the data autonomously, and lead to recursive self-improvement.
Latest News
We are hiring!!
AI 및 IoT에 관심이 있는 학부 인턴생 및 대학원생을 모집합니다!!
대학원생에게는 연구 장비와 연구비(등록금, 생활비 등)를 지원해드리며,
학부 인턴생에게는 프로젝트 참여 기간 및 유형에 따라 연구 장비와 연구비를 지원합니다.
We are actively looking for motivated graduate students in Master’s and Ph.D programs.
Graduate students will be provided with research equipment and grant (tuition, living expenses, etc.).
We have several openings for undergraduate students.
Undergraduate interns are provided with research equipment and grant depending on the duration and type of project participation.
If you are interested in such positions, please do not hesitate to contact us. (whlee@hansung.ac.kr)
Congratulation!!
The new project was selected!!
We will work on the project with receiving financial support by 2025.The new project was selected!!
We will work on the project with receiving financial support by 2029.2022 Best Researcher Award!! (2022학년도 연구영역 Best Researcher상 수상)
2022 Spring Semester Teaching Award!! (2022-1학기 수업평가 우수교원)
We won Best Paper Award in Spring Conference of KINGComputing, 2021!!
10 Latest Published
Papers
Juhyung Lee and Woonghee Lee. “Peak-aware adaptive denoising for Raman spectroscopy based on machine learning approach.” Journal of Raman Spectroscopy 55.4 (2024): 525-533. [SCIE]
Minji Kim, Dongwook Lee, Yongwoo Kwon, and Woonghee Lee. “A Study on Improvement of Federated Learning using Learning Agent and Multi-path transmission” Proc. Korea Information and Communications Society, 2023.
Woonghee Lee. “Reward-based Participant Selection for Improving Federated Reinforcement Learning.” ICT Express 9.5 (2023): 803-808. [SCIE]
Minjeong Lee, Minji Sung, and Woonghee Lee. “A Study on Participant Selection Scheme Based on Network Situation Prediction of Server-to-Device Communication Paths.” Journal of Next-generation Convergence Technology Association, 7.3 (2023): 340~349.
Hyunbae Kim, Chae-Eun Lee, Juhyung Lee, and Woonghee Lee. “A Study on Conducting Federated Learning using Learning Agent” Proc. Korea Information and Communications Society, 2023.
Junwoo Kim and Woonghee Lee. “Analysis of Performance of Federated Learning by Considering Local and Global Trainings in Non-IID Data Environments.” Journal of Next-generation Convergence Technology Association, 7.1 (2023): 21~31.
Hyunbae Kim and Woonghee Lee. “Devising Federated Learning Simulator Considering Learning Agent.” Journal of Next-generation Convergence Technology Association, 6.12 (2022): 2225~2239.
Yaeran Kim and Woonghee Lee. “Distributed Raman Spectrum Data Augmentation System Using Federated Learning with Deep Generative Models.” Sensors, 22.24 (2022): 9900. [SCIE]
Chae-Eun Lee and Woonghee Lee. “Participant Selection Scheme of Federated Learning in Non-IID Data Distribution Environment.” Journal of Next-generation Convergence Technology Association, 6.11 (2022): 2063~2075.
Woonghee Lee. “Federated Reinforcement Learning Based UAV Swarm System for Aerial Remote Sensing.” Wireless Communications and Mobile Computing, vol. 2022, Article ID 4327380, 15 pages, 2022. [SCIE]