姓名：白玉
学历：博士
研究方向：深度强化学习、无人机网络
职务：讲师
邮箱：baiyu01@tyut.edu.cn
教育背景：
2021-11 至 2025-10, 芬兰阿尔托大学, 电气工程, 博士
2018-09 至 2021-06, 电子科技大学, 计算机科学与技术, 硕士
2014-09 至 2018-06, 西南大学, 电子信息工程, 学士
工作背景：
2025-12 至今, 伟德国际1946, 伟德国际1946, 讲师
个人简介：
本人主要从事人工智能赋能的无人机网络与空地协同通信研究，重点运用深度学习、深度强化学习及多智能体强化学习等方法，开展多无人机动态部署、路径规划、自主协同决策与通信资源优化研究。
主要科研成果：
[1] Bai Y, Zhao H, Zhang X, et al. Toward autonomous multi-UAV wireless network: A survey of reinforcement learning-based approaches[J]. IEEE Communications Surveys & Tutorials, 2023. (IF: 46.7, 中国科学院一区 TOP, ESI 高被引)
[2] Bai Y, Yifan Z, Xie B, et al. Age of Information Minimization in UAV-Enabled Integrated Sensing and Communication Systems[J]. IEEE Transactions on Mobile Computing. (CCF A)
[3] Bai Y, Xie B, Ying L, et al. Dynamic UAV Deployment in Multi-UAV Wireless Networks: A Multi-Modal Feature-Based Deep Reinforcement Learning Approach[J]. IEEE Internet of Things Journal, 2025. (中国科学院二区 TOP)
[4] Zhang, Y; Bai, Y*; Zeng, Set al. Backscatter Device-Aided Integrated Sensing and Communication: A Pareto Optimization Framework[J]. IEEE Transactions on Wireless Communications, 2026, 25: 17958-17974.（中国科学院一区）
[5] Bai Y, Chang Z, Jäntti R. Deep Reinforcement Learning-enabled Dynamic UAV Deployment and Power Control in Multi-UAV Wireless Networks[C]//ICC 2024-IEEE International Conference on Communications. IEEE, 2024: 1286-1290. （CCF C）
[6] Bai Y, Xie B, Zhu R, et al. Movable Antenna-Equipped UAV for Data Collection in Backscatter Sensor Networks: A Deep Reinforcement Learning-based Approach[C]//ICC 2025-IEEE International Conference on Communications. IEEE, 2025. （CCF C）
[7] Bai Y, Wang Y, Qiang D, et al. Identification of nanocomposites agglomerates in scanning electron microscopy images based on semantic segmentation[J]. IET Nanodielectrics, 2022, 5(2): 93-103.
