Yu-Ting Li, Kai-Ten Feng, Li-Hsiang Shen, Zhi Ding, and Jen-Ming Wu, “Active Dual STAR-RISs for Full-Duplex MIMO Communications: An Energy-Efficient Optimization Framework,” in IEEE Transactions on Communications, Early Access, Aug. 2026. (International Cooperation with UC Davis, US)

Li-Hsiang Shen and Yu-Quan Zheng, “Aerial Multi-Functional RIS in Fluid Antennas-Aided Full-Duplex Networks: A Self-Optimized Hybrid Deep Reinforcement Learning Approach," in IEEE Open Journal of the Communications Society, Early Access, Aug. 2026. [paper]

Chi-Te Kuo, Li-Hsiang Shen and Jyun-Jhe Huang, “Parametrized Sharing for Multi-Agent Hybrid Deep Reinforcement Learning for Multiple Multi-Functional RISs-Assisted Downlink NOMA Networks,” in IEEE Wireless Communications Letters, vol. 15, pp. 3531-3535, Jun. 2026. [paper]

Li-Hsiang Shen and Jyun-Jhe Huang, “Multi-Functional RIS-Enabled in SAGIN for IoT: A Hybrid Deep Reinforcement Learning Approach with Compressed Twin-Models," in IEEE Internet of Things Journal, vol. 13, no. 5, pp. 9078-9095, Mar. 2026. [paper]

Li-Hsiang Shen, “6D Movable Metasurface (6DMM) in Downlink NOMA Transmissions,” in IEEE Communications Letters, vol. 30, pp. 517-521, 2026. [paper]

Li-Hsiang Shen and Yi-Hsuan Chiu, “Joint Active and Passive Beamforming for Energy-Efficient STARS with Quantization and Element Selection in ISAC Systems," in IEEE Transactions on Communications, vol. 74, pp. 1003-1018, 2026. [paper]

Li-Hsiang Shen, “Liquid Intelligent Metasurface for Fluid Antennas-Assisted Networks," in IEEE Wireless Communications Letters, vol. 14, no. 12, pp. 4192-4196, Dec. 2025. [paper]

Li-Hsiang Shen, Chia-Jou Ku and Kai-Ten Feng, "Robust Active and Passive Beamforming for RIS-Assisted Full-Duplex Systems under Imperfect CSI," in IEEE Open Journal of the Computer Society, vol. 6, pp. 502-518, Apr. 2025. [paper]

Li-Hsiang Shen, Yi-Hsuan Chiu, "RIS-Aided Fluid Antenna Array-Mounted UAV Networks", in IEEE Wireless Communications Letters, vol. 14, no. 4, pp. 1049-1053, Apr. 2025. [paper]

Li-Hsiang Shen, Kai-Ten Feng, Ta-Sung Lee, Yuan-Chun Lin, Shih-Cheng Lin, Chia-Chan Chang and Sheng-Fuh Chang, “AI-Enabled Unmanned Vehicle-Assisted Reconfigurable Intelligent Surfaces: Deployment, Prototyping and Experiments,” in IEEE Network, vol. 38, no. 6, pp. 289-299, Nov. 2024. (Cross-Domain Cooperation with CCU, Taiwan) [paper]

Li-Hsiang Shen, Chia-Jou Ku and Kai-Ten Feng, "Downlink Rate Maximization with Reconfigurable Intelligent Surface Assisted Full-Duplex Transmissions," in IEEE Transactions on Vehicular Technology (Correspondance), vol. 73, no. 8, pp. 12264-12269, Aug. 2024. [paper]

Li-Hsiang Shen, Po-Chen Wu, Chia-Jou Ku, Yu-Ting Li, Kai-Ten Feng, Yuanwei Liu and Lajos Hanzo, "D-STAR: Dual Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surfaces for Joint Uplink/Downlink Transmission," in IEEE Transactions on Communications, vol. 72, no. 6, pp. 3305-3322, Jun. 2024. (International Cooperation with Uni. of Southampton, UK & Queen Mary University of London, UK) [paper]

Li-Hsiang Shen, Kai-Ten Feng, and Lajos Hanzo, “Five Facets of 6G: Research Challenges and Opportunities,” in ACM Computing Surveys, vol. 55, no. 11, pp. 1-39, Feb. 2023. (International Cooperation with Uni. of Southampton, UK) [paper]

Li-Hsiang Shen and Yi-Hsuan Chiu, "Energy-Efficient Coupled STARS with Optimized Quantization and Element Selection in ISAC Systems," in Proceedings of Taiwan Telecommunications Annual Meeting, Taoyuan, Taiwan, Jan. 2026. (Best Paper Award)

Chi-Te Kuo, Li-Hsiang Shen, and Jyun-Jhe Huang, "BP-MAHRL: Bi-Directional Parametrized Sharing Multi-Agent Hybrid DRL for Multiple Multi-Functional RISs-Aided Downlink NOMA Networks," in Proceedings of Taiwan Telecommunications Annual Meeting, Taoyuan, Taiwan, Jan. 2026.

Yu-Ting Li, An-Hung Hsiao, Li-Hsiang Shen, Kai-Ten Feng, You-Cheng Chen, Pei-Hua Wang, Shih-Cheng Lin, and Sheng-Fuh Chang, “Integrated Sensing and Communications for RIS-Assisted Wi-Fi Systems: A Deep Reinforcement Learning Approach,” in Proceedings of IEEE Global Communications Conference (GLOBECOM Workshops), Taipei, Taiwan, Dec. 2025.

Li-Hsiang Shen, Jyun-Jhe Huang, Kai-Ten Feng, Lie-Liang Yang, and Jen-Ming Wu, "Federated Deep Reinforcement Learning for Energy Efficient Multi-Functional RIS-Assisted Low-Earth Orbit Networks", in Proceedings of IEEE International Conference on Communications (ICC), Montreal, Canada, Jun. 2025. [paper]

Chin-Hung Cheng, An-Hung Hsiao, Kai-Ten Feng, and Li-Hsiang Shen, "Reinforcement Learning for Energy Efficient Resource Allocation in ISAC Systems with Integrated WiFi-Radar", in Proceedings of IEEE International Conference on Communications (ICC), Montreal, Canada, Jun. 2025.

Pei-Hsiang Liao, Li-Hsiang Shen, Po-Chen Wu, and Kai-Ten Feng, “Multi-Agent Deep Reinforcement Learning for Energy Efficient Multi-Hop STAR-RIS-Assisted Transmissions,” in Proceedings of IEEE Vehicular Technology Conference (VTC-Fall), Washington DC, USA, Oct. 2024. [paper]

Po-Chen Wu, Li-Hsiang Shen, Kai-Ten Feng, and Chin-Yao Chan, "Federated Reinforcement Learning for Integrated Sensing and Communicaitons with Doubled STAR-RISs," in Proceedings of IEEE International Conference on Communications (ICC), Denver, CO, USA, Jun. 2024.

Yu-Ting Li, Li-Hsiang Shen, Kai-Ten Feng, and Chin-Yao Chan, "Reinforcement Learning for Multi-STAR-RISs with Double-Sided Incidence," in Proceedings of IEEE International Conference on Communications (ICC), Denver, CO, USA, Jun. 2024.

Wei-Yu Chung, Li-Hsiang Shen, Kai-Ten Feng, Yuan-Chun Lin, Shih-Cheng Lin, and Sheng-Fuh Chang, “WiRiS: Transformer for RIS-Assisted Device-Free Sensing for Joint People Counting and Localization using Wi-Fi CSI,” in Proceedings of IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Toronto, Canada, Sep. 2023. [paper]

Chia-Jou Ku, Li-Hsiang Shen, and Kai-Ten Feng, “Reconfigurable Intelligent Surface Assisted Interference Mitigation for 6G Full-Duplex MIMO Communication Systems,” in Proceedings of IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Virtual Conference, Sep. 2022.