Zhize LI
Full-time Faculty
Assistant Professor of Computer Science
School of Computing and Information Systems
SCIS
Qualification
- PhD, Tsinghua University, 2019
Teaching Topics
- Data Structures and Algorithms
- Programming Fundamentals
Research Advisor/Co-Research Advisor to
Research Areas and Areas of Expertise
Strategic Priorities
HighlightsZhize Li is an award-winning computer scientist specializing in optimization and federated learning, with a strong track record in algorithmic innovation, large-scale data analysis, and privacy-preserving machine learning.
Recognized for pioneering efficient and resilient algorithms in federated and distributed learning, bridging theoretical advances with practical solutions for privacy, scalability, and robustness; recipient of multiple prestigious awards including the Tsinghua Outstanding Doctoral Dissertation Award and Rising Star in AI at KAUST; highly active in international research leadership and community service.
Focused research areas include Federated and distributed optimization, communication-efficient algorithms, privacy and resiliency in machine learning, large-scale clustering, nonconvex and stochastic optimization, and theoretical foundations for scalable AI.
Recognized for pioneering efficient and resilient algorithms in federated and distributed learning, bridging theoretical advances with practical solutions for privacy, scalability, and robustness; recipient of multiple prestigious awards including the Tsinghua Outstanding Doctoral Dissertation Award and Rising Star in AI at KAUST; highly active in international research leadership and community service.
Focused research areas include Federated and distributed optimization, communication-efficient algorithms, privacy and resiliency in machine learning, large-scale clustering, nonconvex and stochastic optimization, and theoretical foundations for scalable AI.
Areas of Expertise
Optimization and machine learninglarge-scaledistributedand decentralized optimizationfederated learning (privateefficientand resilient)algorithmic theorycommunication-efficient and privacy-preserving learning.
Past Awarded Grant
- Federated Learning with Limited Bandwidth and Heterogeneous Data, SMU Internal Grant, Ministry of Education (MOE) Tier 1, PI (Project Level): Zhize LI, 2024, S$120,000
- Optimal Compression Algorithms for Large-Scale, High-Dimensional and Multi-criteria Clustering, General Program of National Natural Science Foundation, National Natural Science Foundation of China, Co-PI (Project Level): Zhize LI, 2025, CNY500,000
- Clustering Models, Complexity Analysis and Efficient Algorithms for Large-Scale Data, Key Program of National Natural Science Foundation, National Natural Science Foundation of China, Co-PI (Project Level): Zhize LI, 2024, CNY2,300,000
Latest Publications
Showing up to 6 latest publications from the past 5 years.
- L Huang*, Z Li*, NK Vishnoi*, R Yang*, H Zhao*Neural Information Processing Systems (NeurIPS 2025), 2025
- Q Yao, X Xu, Z LiarXiv preprint arXiv:2508.05568, 2025
- X Xu, Z Li, Y Han, B Wang, J Liu, W WangUSENIX Security Symposium (USENIX Security 2025), 2025
- Z LiInternational Joint Conference on Artificial Intelligence (IJCAI 2025), 2025
- On the trustworthiness of generative foundation models: Guideline, assessment, and perspective [2025]Y Huang, C Gao, S Wu, H Wang, X Wang, Y Zhou, Y Wang, J Ye, J Shi, ...arXiv preprint arXiv:2502.14296, 2025
- H Bao, P Chen, Y Sun, Z LiAAAI Conference on Artificial Intelligence (AAAI 2025), 2025
This highlights are AI-generated content using the faculty's CV.
Qualification
- PhD, Tsinghua University, 2019
Teaching Topics
- Data Structures and Algorithms
- Programming Fundamentals
Research Advisor/Co-Research Advisor to