Bio

Hi! This is Yueqing Liang (梁月清), you can call me Luna as well. I am currently a second-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 data mining and machine learning, including several related topics like fairness, NLP, LLMs, recommender systems, and transfer learning.

News

[07/2023] Be invited to serve as a PC member for AAAI 2024.
[07/2023] Be invited to serve as an external reviewer for ICDM 2023.
[07/2023] Be invited to serve as a PC member for ASONAM 2023.
[06/2023] Attended FAccT 2023 in Chicago.
[06/2023] Be invited to serve as an external reviewer for CIKM 2023.
[05/2023] Attended MMLS 2023 in Chicago.
[04/2023] Be invited to serve as an external reviewer for ECML PKDD 2023.
[02/2023] Be invited to serve as an external reviewer for SIGIR 2023.
[08/2022] Be invited to serve as an external reviewer for WSDM 2022.
[07/2022] Be invited to serve as a co-reviewer for ICDM 2022.
[07/2022] Be invited to serve as a subreviewer for SBP-BRiMS 2022.
[06/2022] Be invited to serve as a subreviewer for DisCoML 2022.
[06/2022] Be invited to serve as a subreviewer for CIKM 2022.
[04/2022] Be invited to serve as a subreviewer for TKDE.
[03/2022] Be invited to serve as a subreviewer for SIGIR 2022.
[02/2022] Be invited to serve as a subreviewer for TCSS.
[02/2022] Be invited to serve as an external reviewer for KDD 2022.
[01/2022] Be invited to serve as a subreviewer for SDM 2022.
[01/2022] Be invited to serve as a subreviewer for Knowledge-Based Systems.
[12/2021] Be invited to serve as a subreviewer for Information & Management.
  

Publications

2023

• Investigating Gender Euphoria and Dysphoria on TikTok: Characterization and Comparison.
  SJ Dillon*, Yueqing Liang*(co-primary), H Russell Bernard, Kai Shu.
  arXiv preprint, May 2023.
  [Paper]

• 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]

• Collaborative Contextualization: Bridging the Gap between Collaborative Filtering and Pre-trained Language Model.
  Chen Wang, Liangwei Yang, Zhiwei Liu, Xiaolong Liu, Mingdai Yang, Yueqing Liang, Philip S. Yu.
  arXiv preprint, Oct 2023.
  [Paper]

2022

• 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 workshop on Trustworthy and Socially Responsible Machine Learning (TSRML@NeurIPS 2022) and workshop on Algorithmic Fairness through the Lens of Causality and Privacy (AFCP@NeurIPS 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]