About me 🐼
Hi there, I'm Siping Shi 👋
I am a postdoctoral fellow with the Department of Computing at The Hong Kong Polytechnic University (PolyU). I obtained my Ph.D. degree in Nov. 2023 from PolyU, supervised by Prof. Dan Wang and collaborated with Prof. Zhu Han and Prof. Yifei Zhu. Prior to that, I received my M.Sc. degree from the University of Chinese Academy of Sciences (UCAS) in 2017, supervised by Prof. Cheng-Zhong Xu, and my B.E. degree from Sichuan University (SCU) in 2014, all in Computer Science. Earlier before I did my Ph.D., I worked two years at Alibaba Group (China) after UCAS.
I am interested in Trustworthy distributed AI systems, focusing on designing efficient, private and robust machine learning systems on distributed environment and resource-constrained edge device, leveraging privacy enhancing technologies (e.g., functional encryption, differential privacy) and robust optimization methods (e.g., distributionally robust optimization). Specific research topics include federated learning, federated analytics, and edge computing for large foundation model.
Research Interests
- Privacy-preserving Large Foundation Models
- Federated Learning/Analytics: Robustness and Privacy
- Distributed Artificial Intelligence (AI) systems
- Edge Computing
Recent News
- (New!) July 6, 2025: Our paper on Accelerating Long Video Understanding via Compressed Scene Graph-Enabled Chain-of-Thought was accepted by ACM MM 2025.
- July 16, 2024: Our paper on Privacy Preserving Federated Learning with Watermarked Image Data was accepted by ACM MM 2024.