Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics. - Yuxin Ma; Tiankai Xie; Jundong Li; Ross Maciejewski (IEEE Trans. Vis. Comput. Graph., 2020)

MultiFair: Multi-Group Fairness in Machine Learning. - Jian Kang; Tiankai Xie; Xintao Wu; Ross Maciejewski; Hanghang Tong (CoRR, 2021)

Auditing the Sensitivity of Graph-based Ranking with Visual Analytics. - Tiankai Xie; Yuxin Ma; Hanghang Tong; My T. Thai; Ross Maciejewski (IEEE Trans. Vis. Comput. Graph., 2021)

InfoFair: Information-Theoretic Intersectional Fairness. - Jian Kang; Tiankai Xie; Xintao Wu; Ross Maciejewski; Hanghang Tong (IEEE Big Data, 2022)

FairRankVis: A Visual Analytics Framework for Exploring Algorithmic Fairness in Graph Mining Models. - Tiankai Xie; Yuxin Ma; Jian Kang; Hanghang Tong; Ross Maciejewski (IEEE Trans. Vis. Comput. Graph., 2022)

DPKnob: A visual analysis approach to risk-aware formulation of differential privacy schemes for data query scenarios. - Shuangcheng Jiao; Jiang Cheng; Zhaosong Huang; Tong Li; Tiankai Xie; Wei Chen 001; Yuxin Ma; Xumeng Wang (Vis. Informatics, 2024)