About Me

I’m currently an AI Resident at Google Research, focusing on federated learning. Before that, I did my undergrad in computer science at the University of Sydney, where I was advised by Prof. Wanli Ouyang and received First Class Honours and the University Medal. I’ve also spent time on various things at Apple, AWS, and Facebook.

I am broadly interested in building, deploying, and facilitating practical intelligent systems for the real world. My recent exploration following this direction focuses on privacy-preserving machine learning via federated learning and differential privacy. In the past, I have also explored multi-agent reinforcement learning and vision-based human action understanding.

Email / LinkedIn / GitHub / Google Scholar


(*equal contribution, alphabetical order)
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation
Peter Kairouz, Ziyu Liu, Thomas Steinke
ICML 2021: International Conference on Machine Learning
Oral Presentation at TPDP 2021
[PDF] [Abstract] [BibTeX] [Talk] [Code]
Learning Implicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning
Meng Zhou*, Ziyu Liu*, Pengwei Sui, Yixuan Li, Yuk Ying Chung
NeurIPS 2020: Conference on Neural Information Processing Systems
[PDF] [BibTeX] [Code]
Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition
Ziyu Liu, Hongwen Zhang, Zhenghao Chen, Zhiyong Wang, Wanli Ouyang
CVPR 2020: Conference on Computer Vision and Pattern Recognition
Oral Presentation
[PDF] [Abstract/Supp] [BibTeX] [Demo] [Code] Star


I have been a teaching assistant for the following courses at the University of Sydney:


Google AI
Resident, Present
Facebook, Menlo Park, United States
Software Engineer Intern, Messenger Ranking, 2019/2020
Amazon Web Services, Sydney, Australia
Software Engineer Intern, Safety Engineering, 2018/2019
Apple, Cupertino, United States
Software Engineer Intern, Core OS, 2018


  • Reviewer, International Journal of Computer Vision (IJCV), 2021.