Zixin Wang

Zixin Wang

Post-doctoral fellow
Dept. ECE

Publications

You can also find my publications in Google Scholar

Journals

  1. Z. Wang, Y. Shi, and K. B. Letaief, “Edge Large AI Models: Collaborative Deployment and IoT Applications,” IEEE IoT Mag., 2025, to appear.
  2. H. Li, S. Xie, J. Shao, Z. Wang, H. He, S. Song, J. Zhang and K. B. Letaief, “Mutual Information-Empowered Task-Oriented Communication: Principles, Applications and Challenges,” submitted to IEEE Commun. Mag., 2025.
  3. Y. Zou, Z. Wang, Y. Zhou, Y. Shi, “Joint Rank Optimization and Bandwidth Allocation for Heterogeneous Federated LoRA Fine-Tuning,” submitted to IEEE Trans. Veh. Technol., 2025.
  4. Z. Wang, Y. Zhou, Y. Shi, and K. B. Letaief, “Federated Fine-Tuning for Pre-Trained Foundation Models Over Wireless Networks,” IEEE Trans. Wireless Commun., 2025, to appear.
  5. Y. Zhao, Y. Zhou, Z. Wang, Y. Shi, N. Cheng, and H. Zhou, “Learning to Beamform for Integrated Sensing and Communication: A Graph Neural Network with Implicit Projection Approach,”IEEE Trans. Wireless Commun., 2025, to appear.
  6. Z. Wang, Y. Zhou, Y. Shi, J. Zhu, and K. B. Letaief, “Edge Large AI Models: Revolutionizing 6G Networks,” IEEE Commun. Mag., 2025, to appear.
  7. X. Long, Y. Jiang, Z. Wang, X. Liu, Y. Shi, and Y. Zhou, “Microservice Migration in Hybrid Satellite-Terrestrial Networks for Autonomous Vehicles,” J. Commun. Info. Netw., 2025, to appear.
  8. Z. Wang, M. Bennis, and Y. Zhou, “Graph Attention-based MADRL for Access Control and Resource Allocation in Wireless Networked Control Systems,” IEEE Trans. Wireless Commun., vol. 23, no. 11, pp. 16076-16090, Nov. 2024.
  9. Z. Wang, Y. Zhou, and Y. Shi, “Over-the-air Federated Graph Learning,” IEEE Trans. Wireless Commun., vol. 23, no. 12, pp. 18669-18683, Dec. 2024.
  10. S. Wan, Z. Wang and Y. Zhou, “Scalable Hybrid Beamforming for Multi-User MISO Systems: A Graph Neural Network Approach,” IEEE Trans. Wireless Commun., vol. 23, no. 10, pp. 13694-13706, Oct. 2024.
  11. Z. Wang, Y. Zou, Q. An, Y. Zhou, Y. Shi, and M. Bennis, “A Graph Neural Network Learning Approach to Optimize RIS-Assisted Federated Learning,” IEEE Trans. Wireless Commun., vol. 22, no. 9, pp. 6092–6106, Sep. 2023.
  12. Y. Zou, Z. Wang, X. Chen, H. Zhou and Y. Zhou, “Knowledge-Guided Learning for Transceiver Design in Over-the-Air Federated Learning,” IEEE Trans. Wireless Commun., vol. 22, no. 1, pp. 270-285, Jan. 2023.
  13. Z. Yang, Y. Shi, Y. Zhou, Z. Wang, and K. Yang, “Trustworthy Federated Learning via Blockchain,” IEEE Int. Things J., vol. 10, no. 1, pp. 92-109, Jan. 2023.
  14. Y. Shi, L. Lian, Y. Shi, Z. Wang, Y. Zhou, L. Fu, L. Bai, J. Zhang, W. Zhang, “Machine Learning for Large-Scale Optimization in 6G Wireless Networks,” IEEE Commun. Sur. Tuts., vol. 25, no. 4, pp. 2088-2132, Fourth Quarter, 2023.
  15. Z. Wang, H. Zhu, M. He, Y. Zhou, X. Luo, and N. Zhang, “GAN and Multi-Agent DRL based Decentralized Traffic Light Signal Control,” IEEE Trans. Veh. Technol., vol. 71, no. 2, pp. 1333-1348, Feb. 2022.
  16. Z. Wang, J. Zong, Y. Zhou, Y. Shi, and V. W.S. Wong, “Decentralized Multi-Agent Power Control in Wireless Networks with Frequency Reuse,” IEEE Trans. Commun., vol. 70, no. 3, pp. 1666-1681, Mar. 2022.
  17. H. Zhu, Z. Wang, F. Yang, Y. Zhou, and X. Luo, “Intelligent Traffic Network Control in the Era of Internet of Vehicles,” IEEE Trans. Veh. Technol., vol. 70. no. 10, pp. 9787-9802, Oct. 2021.

Conferences

  1. H. Yuan, Z. Wang, Y. Jiang, X. Liu, Y. Shi, and T. Wang, “SAI: Latency-aware Satellite Edge LAM Inference with Looped Transformer,” IEEE Int.l’ Conf. Commun. (ICC), Montreal, Canada, Jun. 2025.
  2. T. Kang, Z. Wang, H. He, J. Zhang, S. H. Song, and Khaled B. Letaief, “Federated Low-rank Adaptation with Differential Privacy over Wireless Networks,” IEEE MeditCom, 2025.
  3. Z. Wang, Y. Zhou, Y. Shi, and K. B. Letaief, “Federated Low-Rank Adaptation for Large Language Model Fine-Tuning Over Wireless Networks,” IEEE Global Commun. Conf. (GLOBECOM), Cape Town, South Africa, Dec., 2024.
  4. G. Gao, Q. An, Z. Wang, Z. Wang, Y. Shi, and Y. Zhou, “Over-the-Air Computation Assisted Federated Learning With Progressive Training,” IEEE Int.l’ Conf. Commun. (ICC), Denver, CO, USA, Jun., 2024.
  5. Y. Zhao, Z. Wang, Z. Wang, X. Chen and Y. Zhou, “Learning to Beamform for Dual-Functional MIMO Radar-Communication Systems,” IEEE Int.l’ Conf. Commun. (ICC), Roma, Italy, May, 2023.
  6. Z. Li, Z. Wang, Z. Wang, and Y. Zhou, “Energy-Efficient Federated Learning Over Hierarchical Aerial Wireless Networks,” Annu. Int. Symp. PIMRC, Toronto, Canada, Sept., 2023.
  7. Z. Wang, H. Zhu, Y. Zhou, and X. Luo, “Joint Traffic Signal and Connected Vehicle Control in IoV via Deep Reinforcement Learning,” IEEE WCNC, Nanjing, China, Mar., 2021.
  8. M. He, X. Luo, Z. Wang, F. Yang, H. Qian, and C. Hua, “Global Traffic State Recovery via Local Observations with Generative Adversarial Networks,” IEEE Int. Conf. Acoust. Speech Signal Process. (ICASSP), Barcelona, Spain, May, 2020.