ISLAB

#Wireless Communications #Signal Processing #Machine Learning #Artificial Intelligence

'' ISLab is focusing on machine learning, signal processing, and next-generation mobile communication systems. The research related to machine learning and signal processing includes compressive sensing, sparse signal recovery, matrix completion, financial big data analysis and decision-making using supervised/unsupervised learning, radar/sonar/image signal analysis using reinforcement learning and meta-learning, etc. In relation to mobile communication systems, ISLab conducting research on massive MIMO transmission techniques for 6G mobile communications, ultra-reliable and low-latency communication (URLLC), and the design of future wireless networks based on artificial intelligence. ''

Research Results

Task-oriented communication using LMM

Task-oriented communications for autonomous agent using LMM

Real-time 3D object detection using LiDAR data

Current Research Topics

Computer Vision-aided Communications

Y. Ahn, J. Kim, S. Kim, K. Shim, J. Kim , S. Kim and B. Shim, "Towards Intelligent Millimeter and Terahertz Communication for 6G: Computer Vision-aided Beamforming," IEEE Wireless Communications

Visual Language Models

D. Kim, M. Bae, K. Shim, and B. Shim, "Visually Guided Decoding: Gradient-Free Hard Prompt Inversion with Language Models," International Conference on Learning Representation, 2025.

Terahertz Beam Management

S. Kim, J. Park, J. Moon and B. Shim, "Fast and Accurate Terahertz Beam Management via Frequency-dependent Beamforming", IEEE Transactions on Wireless Communications

Semantic Segmentation

S. Kim, D. Park and B. Shim, "Semantic-aware superpixel for weakly supervised semantic segmentation" In Proceedings of Conference on Artificial Intelligence (AAAI), Vol. 37, No. 1, pp. 1142-1150, 2023.

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