Alumni

邱翊宣 claire90428 at gmail.com (2 year)

• Thesis: Joint Beamforming, Quantization and Element Selection for Energy-Efficient STAR-RIS in Integrated Sensing and Communication Systems (用於整合感測與通訊系統中具能源效益之STAR-RIS的聯合波束成形、量化與元件選擇設計)

• [J1] Li-Hsiang Shen and Yi-Hsuan Chiu, “RIS-Aided Fluid Antenna Array-Mounted AAV Networks,” IEEE Wireless Communications Letters, vol. 14, no. 4, pp. 1049-1053, Apr. 2025.

• [J2] Li-Hsiang Shen and Yi-Hsuan Chiu, “Joint Active and Passive Beamforming for Energy-Efficient STARS with Quantization and Element Selection in ISAC Systems," IEEE Transactions on Communications, Nov. 2025.

• [C1] 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)

• 榮獲「中國電機工程學會-青年論文獎」第三名

• 緯穎 (Wiwynn)

黃雋喆 kenneth90912 at gmail.com (2 year)

• Thesis: Twin Model-Driven Hybrid Deep Reinforcement Learning for Joint Computing and Communications in Multi-Functional RIS-Aided Space-Air-Ground Integrated Networks (雙模型驅動之混合深度強化學習於聯合運算與通訊於多功能RIS輔助之星空地整合網路)

• [C1] 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 Proc. IEEE International Conference on Communications (ICC), Jun. 2025.

• [C2] 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.

• [J1] 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," IEEE Internet of Things Journal, Dec. 2025.

• [J2] 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, 2026.

• 「第十八屆崇越 AI 論文大賞 」入圍決賽評選

• 榮獲「台灣雲端計算學會-最佳博碩士論文獎」碩士組佳作

• 建興儲存科技 (SSSTC)

鄭郁全 wan900627 at gmail.com (2 year)

• Thesis: Hybrid Deep Reinforcement Learning for Multi-Functional RIS-Mounted UAVs in Fluid Antenna-Assisted Full-Duplex Networks (混合深度強化學習用於多功能RIS裝載於無人機之流體天線輔助之全雙工網路)

• [J1] 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," under review, 2026.

• International Studies

柯俞廷 cathy99669 at gmail.com (2 year)

• Thesis: Clustering and Resource Allocation for Hierarchical Federated Learning in Space-Air-Ground Integrated Networks (星空地整合網路中階層聯邦學習之分群與資源分配技術)

• [J1] Li-Hsiang Shen and Yu-Ting Ko, “HFedSAG: DRL-Driven Clustering and Resource Allocation for Hierarchical Federated Learning in Space-Air-Ground Integrated Networks," under review, 2026.

吳軒宇 karta1020165 at gmail.com (2 year)

• Thesis: Fed-HMF: A Federated Learning Framework with Hierarchical Multi-Scale Fusion for Multi-Modal Vehicular Recognition (Fed-HMF: 用於多模態車輛識別之階層式多尺度融合之聯邦學習框架)

• Conf/Journal: To appear

• 緯創 (Wistron)