IISL@HYU

Information and Intelligence Systems Lab (IISL) is a research group in the Department of Electronic Engineering at Hanyang University, affiliated with the Graduate School of Artificial Intelligence Semiconductor. Our research spans artificial intelligence, optimization, statistical inference, and information theory, with a broad range of applications in modern engineering systems. Core topics include (but are not limited to) efficient learning for hyperscale AI, distributed learning, reinforcement learning, AI for wireless communications, large-scale optimization, and statistical signal processing.

OPENINGS

We are actively looking for motivated graduate students interested in machine learning, reinforcement learning, wireless communications, or optimization.
- Openings for AI Algorithms/Optimizations and Reinforcement Learning in the Graduate School of Artificial Intelligence Semiconductor (인공지능반도체 대학원)
- Openings for Machine Learning (Continual Learning/Federated Learning/Many-Task Learning) and 6G Communications in the Department of Electronic Engineering (BK21, Beyond-G Global Innovation Center)

NEWS

[September 2026] Y. Jeong, W. Ko, S.-W. Hong, and S. Hong, "Heterogeneous Multi-Agent Reinforcement Learning for Radio Resource Management under Coupled Finite-Horizon Constraints," submitted to IEEE Internet of Things Journal.
[September 2026] H.-G. Joo, S. Hong, and D.-J. Shin, "TierSecAgg: Tier-Stratified Secure Aggregation for SignSGD-Based Hierarchical Federated Learning in IoT Edge-Cloud Systems," submitted IEEE Internet of Things Journal.
[August 2026] W. Choi, J. Lee, and S. Hong, "Structure-Aware Learning for Rate-Splitting Multiple Access: Efficient Beamforming via Inverse-Free Reconstruction," submitted IEEE Globecom-Workshop.
[August 2026] Y. Jeong, W. Ko, and S. Hong, "On the Timescale of Constraint Regulation in Multi-Agent Reinforcement Learning for Finite-Horizon Wireless Resource Management," submitted to IEEE Globecom-Workshop.
[July 2026] W. Ko, Y. Jeong, S.-W. Hong, and S. Hong, "LyMARL: A Lyapunov-Guided Multi-Agent Reinforcement Learning Framework for Energy-Aware Radio Resource Management," accepted to IEEE Internet of Things Journal.
[July 2026] U. Hwang and S. Hong, "Scalable and Robust Reinforcement Learning through Expectile Regression," accepted to IEEE Transactions on Neural Networks and Learning Systems.
[July 2026] H. Joo, S. Lee, S. Hong, and D.-J. Shin, "Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning," IEEE Internet of Things Journal, vol. 13, no. 18, Sep. 2026.
[July 2026] W. Choi, J. Lee, and S. Hong, "Scalable Rate-Splitting Precoding via Recurrent Structure-Preserving Graph Neural Networks," submitted to IEEE Transactions on Wireless Communications.
[April 2026] J. Lee, J. Seong, S. Hong, W. Shin, M. Z. Win, "Near-Field Propagation Delay-Enabled RIS for Beam-Squint Control in Wideband LEO Satelite Communications," submitted to IEEE Transactions on Wireless Communications (Major Revision).
[January 2026] S.-W. Hong, Y. Jeong, U. Hwang, and S. Hong, "QIPPO/CA: A Quantized Communication-Efficient MARL Framework for Fully Distributed Channel Access in Next-Generation Wireless Networks," IEEE Internet of Things Journal, vol. 13, no. 5, pp. 8615-8627, Mar. 2026.
[January 2026] W. Choi, J. Lee and S. Hong, "CSIT-Free Beamforming for Multi-Group Multicast in Overloaded mmWave Systems," submitted to IEEE Transactions on Wireless Communications.

REPOSITORIES

IISL github repository: click here
IISL presentation repository: click here

CONTACT US

Location: Koo Ja-Kyum Mech. Eng. Bldg., Room 1019, Hanyang University

222 Wangsimni-ro, Seongdong-gu, Seoul, 04763, Korea

Email: snhong at hanyang dot ac dot kr