We introduce BiasEye, a bias-aware real-time interactive material screening visualization system. BiasEye enhances awareness of cognitive biases by improving information accessibility and transparency. It also aids users in identifying and mitigating biases through a machine learning (ML) approach that models individual screening preferences. Findings from a mixed-design user study with 20 participants demonstrate that, compared to a baseline system lacking our bias-aware features, BiasEye increases participants’ bias awareness and boosts their confidence in making final decisions. At last, we discuss the potential of ML and visualization in mitigating biases during human decision-making tasks. Paper from IUI 2024
About Me
I am a 2nd year Master student at School of Information Science and Technology, ShanghaiTech Unvieristy advised by Prof. Quan Li (李权). My reserach interests include:
- Interactive visual analytic systems to prob and mitigate human cognitive biases in decision-making activities
- User-centric Design to enhance the perception of emotional experience
Education Experience
- 2018-2022: Bachelor in ShanghaiTech University, China
- 2022-Now : Postgraduate in ShanghaiTech University, China
Research Projects
Bias-Aware Real-time Interactive Material Screening System
Re-visualizing Music Comments with Map Metaphors
We propose a novel approach that leverages deep learning methods to capture contextual keywords, sentiments, and induced mechanisms from song comments. The study augments a current music app with two features, including the presentation of tags that best represent song comments and a novel map metaphor that reorganizes song comments based on chronological order, content, and sentiment. The effectiveness of the proposed approach is validated through a usage scenario and a user study that demonstrate its capability to improve the user experience of exploring songs and browsing comments of interest. Paper from Journal of Visualization
Publications
BiasEye: A Bias-Aware Real-time Interactive Material Screening System for Impartial Candidate Assessment
Qianyu Liu, Haoran Jiang, Zihao Pan, Qiushi Han, Zhenhui Peng, Quan Li
Proceedings of the 29th International Conference on Intelligent User Interfaces (Proc. ACM IUI 2024), 2024.
Paper
Amplifying the music listening experience through song comments on music streaming platforms
Longfei Chen, Qianyu Liu, Chenyang Zhang, Yangkun Huang, Zhenhui Peng, Haipeng Zeng, Zhida Sun, Xiaojuan Ma, Quan Li
In Proceedings of ChinaVis 2023
Paper