Reinforcing AI and Network

RAIN Lab에서는 인공지능(AI), 머신러닝(ML), 그리고 네트워크가 만나는 지점에서 최첨단 연구를 수행합니다. 오늘날의 시스템은 데이터와 함께 AI 기능을 품는 방향으로 새롭게 설계되고 있습니다. 우리 연구실은 이러한 흐름 속에서 AI 기술 자체의 발전과, 그 지능을 전달하는 AI-Native Network를 함께 연구하며, 지능이 우리의 일상으로 스며들도록 하는 것을 목표로 합니다. 이를 위해 학습과 네트워킹의 효율성과 성능을 높이는 다양한 접근법을 탐구하고 있습니다.

The RAIN Lab (Reinforcing AI and Network) conducts cutting-edge research at the intersection of Artificial Intelligence (AI), Machine Learning (ML), and Networking. As modern systems are redesigned to embed AI functions alongside the data they carry, we work to advance both AI technology itself and the AI-native networks that will deliver it -- bringing intelligence into everyday life. Our research explores a wide range of approaches to improving the efficiency and performance of learning and networking systems.

RAIN Lab에서는 AI/ML과 네트워크 연구에 관심 있는 학부 인턴 및 석·박사과정 대학원생을 모집하고 있습니다. 아래 주제에 관심이 있는 분은 이메일로 편하게 문의해 주시기 바랍니다. (문의시 CV, 성적증명서, 관심연구분야 등을 함께 보내주세요.)
Current openings:

AI-Native Networks: AI를 위한 분산 컴퓨팅, 엣지 컴퓨팅, 위성 네트워크, 스트리밍, (and of your interest)
Machine Learning: 머신 언러닝, 신경망 구조 탐색(NAS), 강화학습, (and of your interest)
Robotics: Vision-Language-Action(VLA) 모델, 학습 기반 플래닝, 다중 로봇 협업

이메일: changhee@korea.ac.kr
Lab: Room 602, Jung Un-oh IT Building, Korea University / 정운오IT교양관 602호

Recent news:

[2026.08] Our paper has been accepted at IEEE Communications Magazine.

Jeongmin Bae, Harim Kang, Taehun Kim, Taegun An, Seunghyun Lee, Junhao Cai, Changhee Joo*, and Kyunghan Lee*, "RXC: Runtime Extra Compression for Time-Critical Content Delivery," accepted, IEEE Communications Magazine (ComMag).

[2026.03] Our paper has been accepted at IEEE TNSE.

Sunjung Kang, V. Tripathi, Changhee Joo, and Christopher G. Brinton, "Buffer Management for Timely Reconstruction: Lower Bounds and Near-Optimal Policies," accepted, IEEE Transactions on on Network Science and Engineering (TNSE).

[2026.03] Our paper has been accepted at Elsevier Neural Networks.

Taegun An and Changhee Joo*, "DAG-NAS: An Explainable Neural Architecture Search Framework for Reinforcement Learning," accepted, Neural Networks.

[2026.03] Our paper has been accepted at WiOpt'26.

Sihyun Choi, Sungbo Eo, Changhee Joo*, and Saewoong Bahk*, "Interference Prediction and Beam Alignment in 5G Indoor mmWave UDNs," accepted, WiOpt, June 2026.

[2026.03] Our 5-year NRF project titled “Development of Multimodal Machine Unlearning Technologies for Global AI Regulatory Compliance” has been awarded for funding.

[2026.03] Dr. Jihyeon Yun joined the Department of Computer Science and Engieering, Kangwon National University as an Assistant Professor. Many congratulations!

[2026.03] Our paper has been accepted at Elsevier ICT Express.

Byoungkyu Ji, Junghyun Han, Daeun Kim, Jihyeon Yun, and Changhee Joo*, "Inter-Satellite Link Technologies and Applications in Low Earth Orbit Satellite Networks," accepted, ICT Express.

[2026.02] Prof. Joo joins the editorial board of IEEE Transactions on Networking.

[2025.12] Our paper has been accepted at Elsevier Computer Networks.

Chengjun Jin, Junhao Cai, Juhyun Park, and Changhee Joo*, "Economic and Strategic Perspectives on CDN Pricing: A Comprehensive Review," accepted, Computer Networks.

[2025.11] Our paper has been accepted at AAAI'26 as an Oral presentation.

Junhao Cai, Taegun An, Chengjun Jin, Sung Il Choi, Juhyun Park, and Changhee Joo*, "HCF: Hierarchical Cascade Framework for Distributed Multi-Stage Image Compression," accepted, AAAI, Jan. 2026.

[2025.1107] Prof. Joo provided an invited talk at CUHK, Hong Kong, titled "RXC: Runtime Extra Compression for Time-Critical Content Delivery."

[2025.10] Our demo paper has been accepted at ACM MobiHoc.

Harim Kang and Changhee Joo*, "Demo: Feedback-Free Adaptive Multimedia Compression at Wireless Edge," to appear, ACM MobiHoc, Oct. 2025.

[2025.09] Our paper has been accepted at Journal of Communications and Networks.

Jihyeon Yun, Taegun An, Bon-jun Ku, Daesub Oh, and Changhee Joo*, "Multi-Agent Adaptive Frequency Block Selection of LEO Satellites for Interference Avoidance," accepted, Journal of Communications and Networks.

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