Prof. ZHANG Jun’s Research on Privacy-Preserving Distributed Learning Published in Nature Communications
A research paper on “Selective Knowledge Sharing for Privacy-Preserving Federated Distillation Without a Good Teacher”, co-authored by Prof. ZHANG Jun, Electronic and Computer Engineering (ECE), and his former PhD student Dr. SHAO Jiawei, was published in leading multidisciplinary journal Nature Communications.
The paper investigates the important topic of privacy-preserving distributed learning. Their proposed method allows multiple clients (e.g. banks, hospitals) to collaboratively train a machine learning model without sharing private data. Compared with existing works, their method substantially reduces communication overhead during the training process, enhances privacy protection, boosts model performance, and allows clients to adopt different models.
The first author, Dr. Shao Jiawei, finished his PhD studies in early 2024 and is now a postdoctoral fellow in Prof. Zhang’s team. Their work was collaborated with Microsoft Research Asia.
About The Hong Kong University of Science and Technology
The Hong Kong University of Science and Technology (HKUST) (https://hkust.edu.hk/) is a world-class research intensive university that focuses on science, technology and business as well as humanities and social science. HKUST offers an international campus, and a holistic and interdisciplinary pedagogy to nurture well-rounded graduates with global vision, a strong entrepreneurial spirit and innovative thinking. Over 80% of our research work were rated “Internationally excellent” or “world leading” in the Research Assessment Exercise 2020 of Hong Kong’s University Grants Committee. We were ranked 3rd in Times Higher Education’s Young University Rankings 2022, and our graduates were ranked 23rd worldwide and among the best from universities from Asia in Global Employability University Ranking and Survey 2021.
