Zhifeng Jiang @ HKUST 江志锋

I am a 4th-year Ph.D. candidate in Department of Computer Science and Engineering, The Hong Kong University of Science and Technology. I am so fortunate to be advised by and collaborate with Prof. Wei Wang. I also work closely with Prof. Bo Li.

My current research explores system design and implementation for privacy-preserving machine learning via federated learning and differential privacy. I am also interested in serverless computing and big data analytics.

Prior to HKUST, I got my Bachelor's degree from Zhejiang University in Computer Science and Technology in 2019. I then also spent time interning at University of California San Diego and Huawei.

a portrait of Zhifeng Jiang

Peer-Reviewed Conference Proceedings

Pisces: Efficient Federated Learning via Guided Asynchronous Training

Zhifeng Jiang, Wei Wang, Baochun Li, Bo Li
In the proceedings of ACM Symposium on Cloud Computing (SoCC) (2022) 

Paper Code HTML Slides Poster

We present an asynchronous FL system for accelerated training. To avoid incurring excessive resource cost and stale training computation, we use a novel scoring mechanism to select participants. We also adapt the pace of model aggregation to dynamically bound the progress gap between the selected clients and the server.

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
IEEE International Conference on Distributed Computing Systems (ICDCS) (2021) 

Best Paper Runner-Up

Paper Code HTML Recording

We present a serverless-based model serving system that automatically partitions a large model across multiple serverless functions. It employs two novel model partitioning algorithms that respectively achieve latency-optimal serving and cost-optimal serving with SLO compliance.

Peer-Reviewed Journals

Towards Efficient Synchronous Federated Training: A Survey on System Optimization Strategies

Zhifeng Jiang, Wei Wang, Bo Li, Qiang Yang
IEEE Transactions on Big Data (TBD) (2022) 

Paper HTML

We survey recent works in addressing the challenges emerging from synchronous FL training and present them following a typical training workflow through three phases: client selection, configuration, and reporting. We also review measurement studies and benchmarking tools.


Taming Client Dropout and Improving Efficiency for Distributed Differential Privacy in Federated Learning

Zhifeng Jiang, Wei Wang, Ruichuan Chen

Paper Slides Code

We present a distributed differentially private FL framework. It uses a novel 'add-then-remove' scheme where a required noise level can be enforced in each FL training round even though some sampled clients may drop out in the end. It also runs as a distributed pipeline architecture that optimally pipelines communication and computation.

Feature Reconstruction Attacks and Countermeasures of DNN training in Vertical Federated Learning

Peng Ye, Zhifeng Jiang, Wei Wang, Bo Li, Baochun Li

Paper Code

We focus on client data with binary features, and show that unless the feature space is exceedingly large, we can precisely reconstruct the binary features in practice with a robust search-based attack algorithm. We also present a defense mechanism that overcomes such binary feature vulnerabilities by misleading the adversary to search for fabricated features.

FLASHE: Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning

Zhifeng Jiang, Wei Wang, Yang Liu

Paper Code

We propose a homomorphic encryption scheme for efficient cross-silo FL. Compared to commonly used HE schemes, we drop the asymmetric-key design and only involves modular addition operations with random numbers. The computation efficiency is further optimized when being combined with sparsification techniques.

Undergraduate Projects

CSDrop: Leveraging Context-Sensitive Decoding to Thwart Return-Oriented Programming

Zhifeng Jiang, Mohammadkazem Taram, Ashish Venkat, Dean M. Tullsen


To thwart Return-Oriented Programming attacks with microarchitecture-level modification, we propose a CPU plugin that enables context-sensitive decoding for securely backing up and validating return addresses. We evaluate its defense capability and runtime efficiency in the gem5 simulator.

Latest News

  • [03/2023] Invited to serve as reviewer for IEEE Transactions on Mobile Computing.
  • [02/2023] Glad to present our work Hyades at Google.
  • [11/2022] Super excited to present our work Pisces at SoCC'22.
  • [10/2022] I will serve as a member in the shadow program committee of EuroSys'23.
  • [10/2022] Our new work takes the initiative to study feature security problems of DNN training in VFL.
  • [09/2022] Our new work Hyades tackles the privacy risks caused by client dropout and the performance bottlenecks of distributed DP in FL.
  • [09/2022] Pisces has been accepted to SoCC '22. Congrats to my co-authors!
  • [06/2022] Our new work Pisces tackles participation selection and aggregation pace control in asynchronous FL.
  • [05/2022] A survey on federated learning has been accepted by IEEE TBD.
  • [05/2022] I serve as a member of the artifact evaluation committee at OSDI '22 and ATC '22.
  • [09/2021] I serve as a member of the artifact evaluation committee at SOSP '21. Moreover, I am invited to be the discussion lead for an artifact.
  • [07/2021] I pass my Ph.D. Qualifying Examination.
  • [07/2021] Gillis is nominated for ICDCS '21 best paper award (3/97). Congrats to my co-authors!
More >


  • [Fall 2022, Fall 2020] Teaching Assistant, COMP3511 Operating System with Prof. Wei Wang.
  • [Fall 2021], Teaching Assistant, COMP4651 Cloud Computing with Prof. Wei Wang.
  • [Spring 2020], Teaching Assistant, COMP4521 Mobile Application Development with Prof. Jogesh K. Muppala.
  • [Fall 2018], Teaching Assistant, Operating System (Educational Reform Class) with Prof. Jiangmin Ji.


Journal Reviewer: IEEE TMC
Shadow Program Committee: EuroSys'23
Artifact Evaluation Committee: SOSP'21, OSDI'22, ATC'22

Honors & Awards

  • [2023] Research Travel Grant from UGC, HK.
  • [2022] Student Travel Scholarship in ACM SoCC.
  • [2021] Best Paper Runner-Up Award in IEEE ICDCS.
  • [2019] Outstanding graduate in Zhejiang Province.
  • [2017] Annual outstanding student in the Dept. of Computer Science and Technology at ZJU.
  • [2017] National Scholarship in China.