Alumni

邱翊宣 claire90428 at gmail.com (2 year; Jun)

• 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)

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

• Journal: To appear

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)

• Conference: 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.

• Journal: To appear

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)

• Journal: To appear

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)

• Journal: To appear

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)

• Journal: To appear