Korea University
AI and Mobility (AIM) Laboratory
Korea University, AIM Laboratory is selected as University ICT Research Center (ITRC), as a Center Leader
Net-Zero CAFE (Connectivity and Autonomy for Future Ecosystem) Research Center
(대학ICT연구센터(ITRC), 탄소중립 미래자율통신 연구센터)
[참여기관: 숙명여자대학교, 아주대학교, 중앙대학교, 한국외국어대학교]
[관련기사] 고려대, 디지털 첨단 분야 연구 핵심 인재 양성에 앞장서다, 대학뉴스, 2024년 8월 5일.Korea University, AIM Laboratory is selected as Software Star-Lab
Quantum AI Empowered Second-Life Platform Technology
(SW스타랩, 퀀텀 인공지능기반 Second-Life 플랫폼 기술)
[관련기사] 과기정통부, 2024년도 SW스타랩 10개 신규 선정, 디지털타임스, 2024년 8월 12일.
본 연구실/연구센터는 함께 연구할 박사과정, 석사과정, 학부인턴을 모집합니다. 관심이 있는 학생은 김중헌 교수(joongheon@korea.ac.kr)에게 메일로 연락바랍니다.
연구주제) 퀀텀인공지능, 생성망기반 강화학습, 자율이동체제어, 에너지효율적인 네트워크 시스템
연구지원) 석박사과정 인건비 100%지원, 학부인턴 성과에 따라 인건비 지원, 국내/해외 학술대회 참석지원, 국내 기술워크샵 참석지원, 국제저널 및 학술대회 논문 참여기회제공
Introduction to the Lab
Korea University, AI and Mobility (AIM) Laboratory is now conducting the research and development (R&D) in following fields,
- Autonomous Mobility: Multi-Agent Reinforcement Learning for UAV, UAM, AUV, and Satellite Networks
- Quantum Machine Learning: Quantum Reinforcement Learning, Quantum Federated Learning, Software Engineering for Quantum Machine Learning
- Networks: Lyapunov Optimization Theory and Applications
Publication Highlights [Magazines, Top-Journals, Top-Conferences]
Fast Quantum Convolutional Neural Networks for Low-Complexity Object Detection in Autonomous Driving Applications
IEEE Transactions on Mobile Computing (2025)AQUA: Hardware-Agnostic Qubit Allocation for Quantum Multi-Programming
IEEE IPDPS (2025)Joint Multi-Agent Reinforcement Learning and Message-Passing for Distributed Multi-UAV Network Management using Conflict Graphs
IEEE/IFIP NOMS (2025)The Matrix: Quantum AI for Interacting Two Worlds in Prioritized Metaverse Spaces
IEEE Communications Magazine (2024)Quantum Multi-Agent Reinforcement Learning is All You Need: Coordinated Global Access in Integrated TN/NTN Cube-Satellite Networks
IEEE Communications Magazine (2024)Quantum Multi-Agent Reinforcement Learning for Autonomous Mobility Cooperation
IEEE Communications Magazine (2024)Spatio-Temporal Multi-Metaverse Dynamic Streaming for Hybrid Quantum-Classical Systems
IEEE/ACM Transactions on Networking (2024)Joint Quantum Reinforcement Learning and Stabilized Control for Spatio-Temporal Coordination in Metaverse
IEEE Transactions on Mobile Computing (2024)Learning Location from Shared Elevation Profiles in Fitness Apps: A Privacy Perspective
IEEE Transactions on Mobile Computing (2024)Joint User Clustering, Beamforming, and Power Allocation for mmWave-NOMA with Imperfect SIC
IEEE Transactions on Wireless Communications (2024)Hands-On Introduction to Quantum Machine Learning
ACM CIKM (2024)Advanced Taxiing Path Guidance using Multi-Agent Reinforcement Learning for Air Traffic Management
IEEE/IFIP WiOpt (2024)EQuaTE: Efficient Quantum Train Engine for Run-Time Dynamic Analysis and Visual Feedback in Autonomous Driving
IEEE Internet Computing (2023)SlimFL: Federated Learning with Superposition Coding over Slimmable Neural Networks
IEEE/ACM Transactions on Networking (2023)Quantum Split Learning for Privacy-Preserving Information Management
ACM CIKM (2023)Logarithmic Dimension Reduction for Quantum Neural Networks
ACM CIKM (2023)Quantum Multi-Agent Meta Reinforcement Learning
AAAI (2023)Supremo: Cloud-Assisted Low-Latency Super-Resolution in Mobile Devices
IEEE Transactions on Mobile Computing (2022)Hierarchical Reinforcement Learning using Gaussian Random Trajectory Generation in Autonomous Furniture Assembly
ACM CIKM (2022)Cooperative Video Quality Adaptation for Delay-Sensitive Dynamic Streaming using Adaptive Super-Resolution
IEEE/IFIP WiOpt (2022)Joint Superposition Coding and Training for Federated Learning over Multi-Width Neural Networks
IEEE INFOCOM (2022)Communication-Efficient and Distributed Learning Over Wireless Networks: Principles and Applications
Proceedings of the IEEE (2021)A Personalized Preference Learning Framework for Caching in Mobile Networks
IEEE Transactions on Mobile Computing (2021)Probabilistic Caching and Dynamic Delivery Policies for Categorized Contents and Consecutive User Demands
IEEE Transactions on Wireless Communications (2021)Joint Distributed Link Scheduling and Power Allocation for Content Delivery in Wireless Caching Networks
IEEE Transactions on Wireless Communications (2020)Understanding the Potential Risks of Sharing Elevation Information on Fitness Applications
IEEE ICDCS (2020)New Challenges of Wireless Power Transfer and Secured Billing for Internet of Electric Vehicles
IEEE Communications Magazine (2019)Seamless Dynamic Adaptive Streaming in LTE/Wi-Fi Integrated Network under Smartphone Resource Constraints
IEEE Transactions on Mobile Computing (2019)Markov Decision Policies for Dynamic Video Delivery in Wireless Caching Networks
IEEE Transactions on Wireless Communications (2019)Dynamic Power Allocation and User Scheduling for Power-Efficient and Delay-Constrained Multiple Access Networks
IEEE Transactions on Wireless Communications (2019)Randomized Adversarial Imitation Learning for Autonomous Driving
IJCAI (2019)SGCO: Stabilized Green Crosshaul Orchestration for Dense IoT Offloading Services
IEEE Journal on Selected Areas in Communications (2018)Wireless Video Caching and Dynamic Streaming Under Differentiated Quality Requirements
IEEE Journal on Selected Areas in Communications (2018)ShmCaffe: A Distributed Deep Learning Platform with Shared Memory Buffer for HPC Architecture
IEEE ICDCS (2018)The Useful Impact of Carrier Aggregation: A Measurement Study in South Korea for Commercial LTE-Advanced Networks
IEEE Vehicular Technology Magazine (2017)REQUEST: Seamless Dynamic Adaptive Streaming over HTTP for Multi-Homed Smartphone under Resource Constraints
ACM Multimedia (2017)Quality-Aware Streaming and Scheduling for Device-to-Device Video Delivery
IEEE/ACM Transactions on Networking (2016)Energy-Efficient Rate-Adaptive GPS-based Positioning for Smartphones
ACM MobiSys (2010)
Contacts
The offices of Prof. Joongheon Kim and the Korea University AIM Laboratory are Engineering Building 214 and New Engineering Hall 508. (본 연구실의 지도교수인 김중헌 교수는 고려대학교 공학관214호에 위치하고 있으며, 학생 연구실은 고려대학교 신공학관 508호에 위치하고 있습니다.)