Bio

Hi, this is Canyu Chen (陈灿宇). I am currently a third-year Ph.D. student in the Department of Computer Science at Illinois Institute of Technology (IIT) since Fall 2021, advised by Prof. Kai Shu. Before joining IIT, I received my B.S. in Computer Science from the University of Chinese Academy of Sciences (UCAS) in 2020.

My research interests focus on Safe and Responsible Large Language Models with the applications in Social Computing and Healthcare. Happy to chat and discuss collaborations. Feel free to contact me via Email (cchen151 AT hawk.iit.edu) or WeChat (ID: alexccychen).

News

  • [09/2023] New preprint Can LLM-Generated Misinformation Be Detected?, [project website]
  • [06/2023] Will attend FAccT 2023 as a volunteer. Welcome to Chicago and glad to connect!
  • [05/2023] One paper accepted at EACL 2023 and will attend online. Welcome to our poster!
  • [04/2023] Glad to be invited by Prof. Lu Cheng to give a talk on AI Fairness at UIC [Slides]
  • [11/2022] Attend NeurIPS 2022 in person. See you at New Orleans!
  • [08/2022] Attend KDD 2022 in person. Glad to meet old friends and make new friends!
  • Publications

    2023

    2022

    • Combating Health Misinformation in Social Media: Characterization, Detection, Intervention, and Open Issues.
      Canyu Chen*, Haoran Wang*, Matthew Shapiro, Yunyu Xiao, Fei Wang, Kai Shu. (*equal contributions)
      arXiv preprint. Nov. 2022.
      [arXiv]

    • When Fairness Meets Privacy: Fair Classification with Semi-Private Sensitive Attributes.
      Canyu Chen, Yueqing Liang, Xiongxiao Xu, Shangyu Xie, Ashish Kundu, Ali Payani, 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).
      [arXiv] [Video] [Slides] [Poster]

    • Artificial Intelligence Algorithms for Treatment of Diabetes.
      Mudassir M. Rashid, Mohammad Reza Askari, Canyu Chen, Yueqing Liang, Kai Shu, Ali Cinar.
      Algorithms 2022.
      [Paper]

    • BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs.
      Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu.
      Advances in Neural Information Processing Systems (NeurIPS 2022), Datasets and Benchmarks Track.
      [code] [arXiv]

    • PyGOD: A Python Library for Graph Outlier Detection.
      Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, George H. Chen, Zhihao Jia, Philip S. Yu.
      arXiv preprint. Apr. 2022.
      [code] [arXiv]

    Talks

    • [04/18/2022] Fairness in AI: An Introduction at UIC [Slides]