我目前是南加州大学（https://usc.edu/）计算机科学系的硕士生。此前在上海交通大学（https://www.sjtu.edu.cn/）获得了计算机科学与技术学士学位。
我对技术相关领域有广泛的兴趣。在上海交通大学，我曾在SysdomLab的陈晨教授指导下，参与一些分布式机器学习系统，特别是联邦学习系统（https://federated.withgoogle.com/）的优化方法相关的研究项目。在阿里巴巴淘天集团的阿里妈妈（https://www.alimama.com/index.htm）实习期间，我的工作则关注推荐算法中的多模态表征应用和CTR精排模型优化。
未来，我希望在自己擅长的领域不断深耕，同时保持开放的心态，迎接新的技术挑战。不论未来的方向如何，我都希望能够解决具有挑战性的问题，并作出实际的贡献。
Boosting Gradient-based Training Diagnosis for Efficient and Accurate Federated Learning
Jiayi Zhang, Zuo Gan, Chen Chen, Zhifeng Jiang, Hao Wang, Yifei Zhu, Quan Chen, and Minyi Guo
IEEE Transactions on Mobile Computing, 2026
Mitigating Server-side Communication Bottlenecks in Distributed Learning with Round-Robin Participant Coordination
Jiayi Zhang, Chen Chen, Zuo Gan, Wei Wang, Bo Li, and Minyi Guo
IEEE Transactions on Networking, 2025
FedCA: Efficient Federated Learning with Client Autonomy
Na Lv, Zhi Shen, Chen Chen, Zhifeng Jiang, Jiayi Zhang, Quan Chen, and Minyi Guo
In Proceedings of the 53rd ACM International Conference on Parallel Processing, 2024
PAS: Towards Accurate and Efficient Federated Learning with Parameter-Adaptive Synchronization
Zuo Gan, Chen Chen, Jiayi Zhang, Gaoxiong Zeng, Yifei Zhu, Jieru Zhao, Quan Chen, and Minyi Guo
In Proceedings of the IEEE/ACM International Symposium on Quality of Service, 2024
如需了解更多关于我的信息，请查看我的简历 https://1drv.ms/b/c/f8430c815c2dfe90/IQC3xyL4pxXHRIFhQbzH4jovASHbWaiahseENDJ3vxJI00g?e=AJJG4G