Bio
Hi there! This is Yueqing Liang (梁月清), you can call me Luna as well. I am currently a first-year Ph.D. student in the Department of Computer Science at Illinois Institute of Technology (IIT) since Spring 2022, advised by Prof. Kai Shu. Before joining IIT, I received my M.S. in Big Data in Business from the University of Sydney (USYD) in 2020, and my B.E. in Telecommunications Engineering with Management from Queen Mary University of London (QMUL) in 2018.
My research interests are in the broad areas of machine learning and data mining, including several related topics like fairness, recommender system, and transfer learning.
News
Publications
2022
Fair Classification via Domain Adaptation: A Dual Adversarial Learning Approach.
Yueqing Liang, Canyu Chen, Tian Tian, Kai Shu.
Frontiers in Big Data 5, 129. Jan. 2023.
[Paper]Artificial Intelligence Algorithms for Treatment of Diabetes.
Mudassir M. Rashid, Mohammad Reza Askari, Canyu Chen, Yueqing Liang, Kai Shu, Ali Cinar.
Algorithms 2022, 15(9), 299.
[Paper]On Fair Classification with Mostly Private Sensitive Attributes.
Canyu Chen, Yueqing Liang, Xiongxiao Xu, Shangyu Xie, Yuan Hong, Kai Shu.
Advances in Neural Information Processing Systems(NeurIPS), Workshop, 2022.
[Paper]
2021
- Pre-training Graph Neural Network for Cross Domain Recommendation.
Chen Wang, Yueqing Liang, Zhiwei Liu, Tao Zhang, Philip S. Yu.
IEEE CogMI. 2021.
[Paper]