Be brave! Be bold! Be yourself!

College of Computer,
National University of Defense Technology~(NUDT)
Changsha, China
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Hui Zeng

Hui Zeng currently is a Ph.D student in School of Computer at National University of Defense Technology (NUDT), advised by Prof. Zhiping Cai. Previously, I received my bachelor degree (Software Engineering) at Sun Yat-sen University (SYSU), and my master degree at NUDT. My current interests including Federated learning, One-shot Federated Learning, Backdoor Attacks, Security of AIGC.

Publications

2024

• [JPDC] Hui Zeng, Tongqing Zhou, Yeting Guo, Zhiping Cai* and Fang Liu. “Towards Value-sensitive and Poisoning-proof Model Aggregation for Federated Learning on Heterogeneous Data”. Journal of Parallel and Distributed Computing~(JPDC).
  (CCF-B)
  [Paper]

• [ACM MM] Hui Zeng, Minrui Xu, Tongqing Zhou*, Xinyi Wu, Jiawen Kang, Zhiping Cai*, Dusit Tao Niyato. “One-shot-but-not-degraded Federated Learning”. in Proceedings of ACM International Conference on Multimedia~(ACM MM).
  (CCF-A)
  [Paper] [Appendix] [Code]

2023

• [IoTJ] Wu, Hongjia, Hui Zeng, Tongqing Zhou*, Zhiping Cai*, Zehui Xiong, Dusit Tao Niyato and Zhu Han. “From Eye to Brain: A Proactive and Distributed Crowdsensing Framework for Federated Learning.” IEEE Internet of Things Journal (IoTJ) (2023): 8202-8214.
  (Q1, CCF-C)
  [Link]

2022

• [SRDS] Hui Zeng, Tongqing Zhou*, Xinyi Wu, Zhiping Cai*. “Never Too Late: Tracing and Mitigating Backdoor Attacks in Federated Learning.” Proc. of IEEE International Symposium on Reliable Distributed Systems (SRDS) (2022): 69-81.
  (CCF-B, acceptance rate=23%) Best paper candidate!!
  [Paper] [Presentation] [Code]

2021

• [ICPP] Hui Zeng, Tongqing Zhou*, Yeting Guo, Zhiping Cai* and Fang Liu. “FedCav: Contribution-aware Model Aggregation on Distributed Heterogeneous Data in Federated Learning.” Proc. of International Conference on Parallel Processing (ICPP) (2021): 1-10.
  (CCF-B, acceptance rate=26.4%)
  [Paper] [Presentation] [Code]
• [Ubicomp] Guo, Yeting, Fang Liu*, Zhiping Cai, Hui Zeng, Li Chen, Tongqing Zhou and Nong Xiao*. “PREFER: Point-of-interest REcommendation with efficiency and privacy-preservation via Federated Edge leaRning.” Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 5 (2021): 13:1-13:25. (CCF-A)
  [Paper]

Awards

• [Best Paper Candidate] The 41st IEEE International Symposium on Reliable Distributed Systems, 2022.
• [National Scholarship, 2017]
• [National Scholarship, 2018]

Projects

• [Distributed Data Management Module in HarmonyOS] Aug. 2022 - Jun 2023