معرفی
Zhize Li is a tenure-track Assistant Professor at the School of Computing and Information Systems, Singapore Management University (since Nov 2023), focusing on optimization, federated learning, and AI privacy. Previously, he held research roles at Carnegie Mellon University, King Abdullah University of Science and Technology (KAUST), and visiting positions at Duke University and Georgia Institute of Technology.
Education:
- PhD in Computer Science, Tsinghua University (2019)
- MTech, National University of Singapore
- BEng, Shanghai Jiao Tong University
Research Interests: Zhize Li’s work centers on large-scale/distributed/decentralized optimization and private/efficient/resilient federated learning. His research addresses challenges in communication compression, data heterogeneity, and privacy-preserving analytics in AI systems.
Publication Trends: His recent articles focus on federated learning frameworks (e.g., X-VFL, SoteriaFL), optimization algorithms (e.g., SIFAR, DESTRESS), and privacy/security in distributed settings (e.g., data reconstruction attacks, three-point compressors). Keywords include Artificial Intelligence, Machine Learning, Privacy-Preserving, and Optimization.
Scientific Awards:
- Rising Star in AI, KAUST AI Initiative (2022)
- Tsinghua University Outstanding Doctoral Dissertation Award (2019)
- National Scholarship (top 1%, 2018)
- Pacesetter of Outstanding Graduates (2014)
Advising and Grants: Zhize Li actively recruits fully-funded PhD students, visiting scholars, and research engineers. While specific grants are not detailed, his work has been supported by multiple top-tier publications in journals like JMLR and conferences such as NeurIPS, ICML, and AAAI.
