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Zhifeng Jiang
江志锋

Ph.D. graduate from CSE, HKUST


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Zhifeng_Jiang

Last Updated: November 2024

About Me

I am a recent PhD graduate from Computer Science and Engineering, Hong Kong University of Science and Technology. advised by Prof. Wei Wang. I also work closely with Dr. Ruichuan Chen and Prof. Bo Li. I got my B.S. degree in Computer Science from Zhejiang University in 2019.

Research Interests: Privacy Preserving Machine Learning

Dissertation: "Towards Private and Efficient Cross-Device Federated Learning"


News

  • 2024-11: One paper accepted to ACM PPoPP 2025. Congrats to my co-authors!
  • 2024-09: Invited to serve as a reviewer for IEEE TNNLS.
  • 2024-08: Presented our work Lotto at USENIX Security 2024.
  • 2024-08: Given an invited talk in a seminar at Shanghai Jiao Tong University.
  • 2024-07: Given an invited talk in an online seminar of Huawei.
  • 2024-07: Won HKUST RedBird Academic Excellence Award.
  • 2024-07: Received Research Travel Grant from UGC, Hong Kong.
  • 2024-06: Given an invited talk at Shenzhen Institute of Computing Sciences.
  • 2024-06: One paper accepted to ICPP 2024. Congrats to my co-authors!
  • 2024-05: Defended my PhD thesis successfully.
  • 2024-05: Served as an invited reviewer for IEEE Transactions on Big Data.
  • 2024-04: Presented our work Dordis at ACM EuroSys 2024.
  • 2024-04: Received Research Travel Grant from UGC, Hong Kong.
  • 2024-03: Lotto accepted to USENIX Security 2024. Congrats to my collaborators!

Selected Papers

  • USENIX Security'24 Lotto: Secure Participant Selection against Adversarial Servers in Federated Learning
    Zhifeng Jiang, Peng Ye, Shiqi He, Wei Wang, Ruichuan Chen, Bo Li
  • [pdf] [full version] [code] [html] [video] [slides] [bibtex]
  • IEEE TBD'23 Towards Efficient Synchronous Federated Training: A Survey on System Optimization Strategies
    Zhifeng Jiang, Wei Wang, Bo Li, Qiang Yang
  • [pdf] [code] [html] [bibtex]
  • ACM SoCC'22 Pisces: Efficient Federated Learning via Guided Asynchronous Training
    Zhifeng Jiang, Wei Wang, Baochun Li, Bo Li
  • [pdf] [code] [html] [slides] [poster] [bibtex]
  • IEEE ICDCS'21 Gillis: Serving Large Neural Networks in Serverless Functions with Automatic Model Partitioning
    Minchen Yu, Zhifeng Jiang, Hok Chun Ng, Wei Wang, Ruichuan Chen, Bo Li
  • [pdf] [code] [html] [recording] [bibtex]
    Best Paper Runner-Up Award

Other Recent Papers

  • ACM PPoPP'25 SGDRC: Software-Defined Dynamic Resource Control for Concurrent DNN Inference on NVIDIA GPUs
    Yongkang Zhang, Haoxuan Yu, Chenxia Han, Cheng Wang, Baotong Lu, Zhifeng Jiang, Yang Li, Xiaowen Chu, Huaicheng Li
  • [bibtex]
  • ICPP'24 FedCA: Efficient Federated Learning with Client Autonomy
    Na Lv, Zhi Shen, Chen Chen, Zhifeng Jiang, Jiayi Zhang, Quan Chen, Minyi Guo
  • [html] [bibtex]
  • arXiv'22 Feature Reconstruction Attacks and Countermeasures of DNN training in Vertical Federated Learning
    Peng Ye, Zhifeng Jiang, Wei Wang, Bo Li, Baochun Li
  • [preprint] [code]
  • arXiv'21 FLASHE: Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning
    Zhifeng Jiang, Wei Wang, Yang Liu
  • [preprint] [code]

Experience

  • Research Intern, University of California, San Diego, La Jolla, CA, USA, Jul - Sept 2018
    Project: Defense against Return-Oriented Programming

Honors & Awards & Grants

  • RedBird Academic Excellence Award (HKUST, 2024, 2023)
  • Research Travel Grant (UGC, Hong Kong, 2024×2, 2023)
  • Travel Grant (ACM EuroSys, 2024)
  • Student Travel Scholarship (ACM SoCC, 2022)
  • Best Paper Runner-Up Award (IEEE ICDCS, 2021)
  • Outstanding Graduate (Zhejiang Province, 2019)
  • He Zhijun Scholarship (Dept. of CS, ZJU, 2017)
  • National Scholarship (Ministry of Education, China, 2017)

Professional Service

  • Journal Sub-Reviewer: IEEE Transactions on Network Science and Engineering, IEEE Transactions on Dependable and Secure Computing, IEEE Transactions on Big Data
  • Conference Sub-Reviewer: IEEE INFOCOM 2020-2024, IEEE ICDCS 2024, 2023 and 2021, IEEE/ACM IWQoS 2020-2021, IEEE WoWMoM 2021, IEEE ICNP 2020