I am currently a second-year Ph.D. candidate at Shanghai Jiao Tong University (SJTU), supervised by Prof. Zhenzhe Zheng and Prof. Fan Wu. Before that, I received my Bachelor degree in Computer Science from SJTU, 2022.
My research interest focuses on on-device machine learning system. Specifically, I am interested in designing efficient and effective data utilization/processing systems for resource-constrained devices to support data-efficient on-device learning.
📖 Educations
- 2022.09 - Now, Ph.D. Candidate, Department of Computer Science and Engineering, Shanghai Jiao Tong University.
- 2018.09 - 2022.06, IEEE Honored Class (major in computer science), Shanghai Jiao Tong University.
📝 Publications
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Preprint
A Two-Stage Data Selection Framework for On-Device Model Training.
Chen Gong, Zhenzhe Zheng, Fan Wu, Guihai Chen.
Under Review.
[PDF] –An effective & efficient data selection pipeline for on-device ML. -
MobiCom 2024
Delta: A Cloud-assisted Data Enrichment Framework for On-Device Continual Learning.
Chen Gong, Zhenzhe Zheng, Fan Wu, Guihai Chen.
International Conference on Mobile Computing and Networking (MobiCom), 2024. Acceptance Rate=20.8%(103/494). [CCF-A]
[PDF | Code] –A private & efficient data enrichment framework for on-device continual ML. -
ToN 2024
ODE: An Online Data Selection Framework for Federated Learning in Mobile Network.
Chen Gong, Zhenzhe Zheng, Fan Wu, Yunfeng Shao, Bingshuai Li, Guihai Chen.
IEEE/ACM Transactions on Networking (ToN), 2024. [CCF-A]
[PDF | Code] -
WWW 2023
To Store or Not? Online Data Selection for Federated Learning with Limited Storage.
Chen Gong, Zhenzhe Zheng, Fan Wu, Yunfeng Shao, Bingshuai Li, Guihai Chen.
ACM Web Conference (WWW), System Track, 2023. Acceptance Rate=19.2%(365/1900). [CCF-A]
[PDF | Slides | Video | Code] – A collaborative data selection system for multiple devices in FL. -
MM 2023
Fine-Grained Music Plagiarism Detection: Revealing Plagiarists through Bipartite Graph Matching and a Comprehensive Large-Scale Dataset.
Wenxuan Liu, Tianyao He, Chen Gong, Ning Zhang, Hua Yang, Junchi Yan.
ACM International Conference on Multimedia (MM), 2023. Acceptance Rate=29.3%. [CCF-A]
[PDF | Code] – A bipartite graph matching algorithm for music plagisrism detection. -
DASFAA 2021
Modeling Dynamic Social Behaviors with Time-Evolving Graphs for User Behavior Predictions.
Tianzi Zang, Yanmin Zhu, Chen Gong, Haobing Liu, Bo Li.
International Conference on Database Systems for Advanced Applications (DASFAA), 2021. [CCF-B]
[PDF]
💻 Internships
- 2021.09 - 2022.09, Huawei Noah’s Ark Lab, Beijing, China. “面向异构多终端的联邦学习技术”, 优秀结题.
- 2024.06 - Now, ByteDance - App Infra - Client AI, Hangzhou, China. “移动端用户特征构建加速”