清华大学电子工程系微纳光电子学实验室欢迎您! English

杨展鹏

博士后


通讯地址:

清华大学罗姆电子工程馆2-108

北京市海淀区,100084

Tel:+86-10-62783389

Fax:+86-10-62797073-808

电子邮箱:yangzhp@mail.tsinghua.edu.cn

教育经历:

2020-2025 上海科技大学 博士

2016-2020 西安电子科技大学 学士

工作经历:

2025-至今:清华大学电子工程系 博士后

科研工作:

博士期间的主要围绕边缘人工智能的关键技术开展研究,基于区块链、联邦学、微服务服务等技术实现高性能、高可靠、低时延的边缘人工智能模型训练与推理方法,并在此系统架构下设计基于人工智能的资源优化算法,高效分配其感知、计算与通信资源。博后期间则进一步聚焦于实时光谱成像芯片的关键科学问题及集成技术研究,针对工业场景下光电检测系统设计人工智能训练与推理方法,提升光电检测任务的实时性与准确性。

代表性成果:

[1] Chen Lin, Zhanpeng Yang, Ting Wang, Xin Liu, Yuning Jiang, Yong Zhou and Yuanming Shi , “Large Language Models for Microservice Deployment in Space Computing Power Networks”, in Proc. Globecom Workshops (GC Wkshps), Taipei, Taiwan, Dec. 2025.

[2] Z. Yang, P. Zhang, J. Zhu, D. Wen, Y. Shi and W. Chen, “Hierarchical Feder ated Learning with Integrated Sensing-Communication-Computation over Space-Air Ground Integrated Networks,” in Proc. IEEE Int. Conf. Commun. (ICC), Montreal, Canada, Jun. 2025.

[3] Z. Yang, Z. Yu, X. Liu, D. Wen, Y. Zhou and Y. Shi, “Latency-Aware Microservice Deployment for Edge AI Enabled Video Analytics,” in Proc. IEEE Wireless Commun. Netw. Conf. (WCNC), Dubai, United Arab Emirates, Apr. 2024.

[4] Z. Yang,Y. Shi, Y. Zhou, Z. Wang, K. Yang, “Trustworthy federated learning via blockchain,” IEEE Internet Things J.,, vol. 10, no. 1, pp. 92-109, Jan. 2023.

[5] Z. Yang, Y. Zhou, Y,Wu, Y. Shi, “Communication-efficient quantized SGD for learning polynomial neural network,” in Proc. IEEE Int. Perform., Comput., Commun. Conf. (IPCCC), Oct. 2021.

Y. Shi, K. Yang, Z. Yang, and Y. Zhou, “Mobile edge artificial intelligence: Opportunities and challenges,” Elsevier, Aug. 2021.