姓名:王烟濛
职称:讲师
部门:计算机技术研究所
研究方向:边缘智能、联邦学习、分布式优化
邮箱:yanmengwang@njupt.edu.cn
个人简介:
王烟濛,女,南京邮电大学校聘副教授。博士毕业于香港中文大学(深圳)计算机与信息工程专业,获香港中文大学博士学位,博士导师为IEEE Fellow张纵辉教授。2024年4月,加入南京邮电大学计算机学院、软件学院、网络空间安全学院,主要研究方向包括:边缘智能、联邦学习、分布式优化等。近年来,已在IEEE JSAC、IEEE TNNLS、IEEE IoT、IEEE TVT等高水平国际期刊和AAAI、IEEE ICASSP等国际顶级学术会议上发表论文10余篇,并受邀担任IEEE JSAC、IEEE TNNLS、IEEE TSP、IEEE TVT、IEEE ICASSP等多个国际期刊及会议的审稿人。
科研成果:
Ø 期刊论文
[1] Yanmeng Wang, Yanqing Xu, Qingjiang Shi, and Tsung-Hui Chang*, “Quantized federated learning under transmission delay and outage constraints,” IEEE Journal on Selected Areas in Communications (JSAC), 2022, 40(1): 323-341.(CCF-A)
[2] Yanmeng Wang, Qingjiang Shi, and Tsung-Hui Chang*, “Why batch normalization damage federated learning on non-iid data?,” IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2025, 36(1): 1692-1706.(CCF-B)
Ø 会议论文
[1] Yanmeng Wang, Qingjiang Shi and Tsung-Hui Chang, “Batch normalization damages federated learning on non-iid data: Analysis and remedy,” IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023.(CCF-B)
[2] Yanmeng Wang, Yanqing Xu, Qingjiang Shi and Tsung-Hui Chang, “Robust federated learning in wireless channels with transmission outage and quantization errors,” IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2021.
[3] Zhiwei Tang, Yanmeng Wang, and Tsung-Hui Chang, “z-SignFedAvg: A unified sign-based stochastic compression for federated learning,” AAAI Conference on Artificial Intelligence (AAAI), 2024.(CCF-A)