This is Feng Yu, a second-year PhD student in computer science at the University of Exeter, under the supervision of Prof. Jia Hu and Prof. Geyong Min. My research interests are mainly federated learning (FL), continual learning (CL), foundation models (FMs) and edge artificial intelligence (Edge AI).
My research is supported by China Scholarship Council and University of Exeter Scholarships.
Currently, I am interested in variety of issues in federated learning and continual learning such as
Exploring and leveraging large-scale heterogeneous data thoroughly;
Advancing continual learning in the context of resource-constrained FL settings;
Developing lightweight and efficient fine-tuning techniques for FMs tailored to Edge AI applications.
My previous research works cover federated learning, deep reinforcement learning, blokchain, generative adversarial network, differential privacy and privacy protection.
I am open to discussing research ideas and seeking academic collaborations. Drop me email if interested!
News
Nov 20, 2024
The first comprehensive survey FCL for Edge-AI has been released!
Sep 1, 2023
Started my PhD at Exeter!
Selected publications
2024
Federated Continual Learning for Edge-AI: A Comprehensive Survey
Zi Wang,
Fei Wu,
Feng Yu
,
Yurui Zhou,
Jia Hu,
and Geyong Min
@article{zi2024federated,title={Federated Continual Learning for Edge-AI: A Comprehensive Survey},author={Wang, Zi and Wu, Fei and Yu, Feng and Zhou, Yurui and Hu, Jia and Min, Geyong},journal={arXiv preprint arXiv:2411.13740},year={2024},bibtex_show={true},selected={true},html={https://arxiv.org/abs/2411.13740}}
2023
Communication-Efficient Personalized Federated Meta-Learning in Edge Networks
Feng Yu
,
Hui Lin,
Xiaoding Wang,
Sahil Garg,
Georges Kaddoum,
Satinder Singh,
and Mohammad Mehedi Hassan
IEEE Transactions on Network and Service Management
2023
@article{yu_communication-efficient_2023,title={Communication-Efficient Personalized Federated Meta-Learning in Edge Networks},copyright={4.758},issn={1932-4537},doi={10.1109/TNSM.2023.3263831},journal={IEEE Transactions on Network and Service Management},author={Yu, Feng and Lin, Hui and Wang, Xiaoding and Garg, Sahil and Kaddoum, Georges and Singh, Satinder and Hassan, Mohammad Mehedi},year={2023},pages={1--1},html={https://doi.org/10.1109/tnsm.2023.3263831},bibtex_show={true},abbr={TNSM},selected={true}}
2022
Blockchain-empowered secure federated learning system: Architecture and applications
Feng Yu
,
Hui Lin,
Xiaoding Wang,
Abdussalam Yassine,
and M. Shamim Hossain
@article{YU202255,title={Blockchain-empowered secure federated learning system: Architecture and applications},journal={Computer Communications},volume={196},pages={55-65},year={2022},issn={0140-3664},doi={https://doi.org/10.1016/j.comcom.2022.09.008},url={https://www.sciencedirect.com/science/article/pii/S0140366422003474},author={Yu, Feng and Lin, Hui and Wang, Xiaoding and Yassine, Abdussalam and Hossain, M. Shamim},html={https://doi.org/10.1016/j.comcom.2022.09.008},pdf={bfl_comcom2022.pdf},bibtex_show={true},abbr={COMCOM},selected={true}}
