Yueqing is a scholarship recipient of the ARC Centre for Automated Decision-Making and Society.

Each year the Centre offers a select number of PhD scholarships across our nodes to engage and prepare the next generation of researchers to make world-leading contributions in an increasingly engaged and transdisciplinary research environment.

Thesis Title
Fairness-Aware and Privacy-Preserving Recommender System 

Research Description
This project will propose a novel fairness-aware and privacy-preserving recommender system that is based on adversarial machine learning and attack/defence models. Specifically, the proposed recommender system aims at implementing individual-level fairness and simultaneously, providing privacy protection such that an adversary cannot uncover private information about users from recommendation results. The project will further leverage Generative Adversarial Networks (GAN) and propose attack models on both user embedding level and user profile level to generate better adversarial examples for the purpose of adversarial training on recommender systems. It also aims at incorporating text mining techniques to explore the fairness of user complaints to an individual provider. 

Yueqing also has research experience in Natural Language Processing, which is a relevant technology that is planned to be used in this project to explore the fairness of users in recommender systems.

Assoc Prof Jeffrey Chan, RMIT University
Prof Mark Sanderson, RMIT University