Yuhang Yao

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Porter Hall B23

Carnegie Mellon University

Pittsburgh, PA 15213

I am currently a fifth-year Ph.D. candidate in Electrical Computer Engineering at Carnegie Mellon University, working with Prof. Carlee Joe-Wong who leads the Learning, Incentives, and Optimization for Networked Systems(LIONS) research group. My research interests include Federated Graph Learning and Federated Learning with Generative AI.

Before joining CMU, I earned my Bachelor of Science degree in Computer Science and Electrical Engineering at the IEEE Honor Class from Shanghai Jiao Tong University, supervised by Prof. Xinbing Wang and Luoyi Fu, in 2019.

I am always open to collaborations, both academia and industry. If you have some interesting ideas, feel free to contact me!

News

Feb 15, 2024 We are developing FedGraph library for federated graph learning.
Feb 01, 2024 I join FEDML AI as a research scientist intern for generative AI.
Dec 10, 2023 FedGCN and WyzeRule are accepted by NeurIPS. FedML-HE gets accepted by FL-NeurIPS workshop.

Selected Publications

  1. NeurIPS
    FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks
    Yuhang Yao, Weizhao Jin , Srivatsan Ravi , and 1 more author
    Advances in Neural Information Processing Systems, 2024
  2. NeurIPS
    Wyze Rule: Federated Rule Dataset for Rule Recommendation Benchmarking
    Mohammad Mahdi Kamani , Yuhang Yao, Hanjia Lyu , and 5 more authors
    Advances in Neural Information Processing Systems, 2024
  3. IoTDI
    FedRule: Federated Rule Recommendation System with Graph Neural Networks
    Yuhang Yao, Mohammad Mahdi Kamani , Zhongwei Cheng , and 3 more authors
    In Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation , 2023