牛泽坤

Zekun niu

研究方向：基于Python的智能光纤仿真平台的开发
博士研究生在读（ 2018 —— 至今 ）

电子邮箱：zekunniu@sjtu.edu.cn

上海交通大学2020级电子信息与电气工程学院电子系博士生。本科期间曾担任学院年级会年级长、学院学生会学习部部长等职务，负责组织过ACM竞赛、手游开发竞赛等多项学术活动。目前研究基于深度学习研究光纤非线性的补偿和性能优化技术，以AI为抓手，结合光通信专业知识，设计最优化光传输系统，提升通信性能极限。基于Python语言设计并开发了初版的IFTS平台，实现了完整的光通信算法库，融合光通信算法与AI算法，为光通信领域内高效智能的科学计算提供有效支撑。

论文：

[1] Z. Niu, H. Yang, H. Zhao, C. Dai, W. Hu and L. Yi, "End-to-End Deep Learning for Long-haul Fiber Transmission Using Differentiable Surrogate Channel," in Journal of Lightwave Technology, 2022.

[2] H. Yang, Z. Niu, et al., "Fast and Accurate Optical Fiber Channel Modeling Using Generative Adversarial Network," in Journal of Lightwave Technology, vol. 39, no. 5, pp. 1322-1333, 1 March1, 2021.

[3] H. Yang, Z. Niu, et al., "Fast and Accurate Waveform Modeling of Long-Haul Multi-Channel Optical Fiber Transmission Using a Hybrid Model-Data Driven Scheme," in Journal of Lightwave Technology, 2022.

[4] H. Yang, H. Zhao, Z. Niu, et al., "Low-complexity full-field ultrafast nonlinear dynamics prediction by a convolutional feature separation modeling method," in Optics Express, 2022.

[5] N. Zhang H. Yang, Z. Niu, et al., "Transformer-Based Long Distance Fiber Channel Modeling for Optical OFDM Systems," in Journal of Lightwave Technology, 2022.

专利：

[1] 义理林，杨航，牛泽坤，基于数据驱动的光纤通信实验系统端到端建模方法和系统，CN202211281083.7

[2] 义理林，杨航，牛泽坤，基于特征解耦的分布式光纤信道快速精确建模方法和系统，CN202111478750.6

[3] 义理林，牛泽坤，杨航，基于可微辅助信道的端到端优化方法及系统，CN202111405475.5

[4] 义理林，牛泽坤，戴辰昊，杨航，基于深度学习的光纤通信传输系统互信息量计算方法及系统，CN202210540923.0

[5] 义理林，牛泽坤，梁家熙，基于互信息量估计的几何与概率联合星座整形方法及系统，CN202210010298.9

[6] 义理林，梁家熙，牛泽坤，基于互信息量估计神经网络的物理层保密方法及系统，CN202111574717.3

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