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 008; 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 008; 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 008; Hanghang Tong; Ross Maciejewski (IEEE Trans. Vis. Comput. Graph., 2022)

Evaluating Loss Landscapes from a Topology Perspective. - Tiankai Xie; Caleb Geniesse; Jiaqing Chen; Yaoqing Yang; Dmitriy Morozov; Michael W. Mahoney; Ross Maciejewski; Gunther H. Weber (CoRR, 2024)

Visualizing Loss Functions as Topological Landscape Profiles. - Caleb Geniesse; Jiaqing Chen; Tiankai Xie; Ge Shi 007; Yaoqing Yang; Dmitriy Morozov; Talita Perciano; Michael W. Mahoney; Ross Maciejewski; Gunther H. Weber (CoRR, 2024)

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)

LossLens: Diagnostics for Machine Learning Through Loss Landscape Visual Analytics. - Tiankai Xie; Jiaqing Chen; Yaoqing Yang; Caleb Geniesse; Ge Shi 007; Ajinkya Chaudhari; John Kevin Cava; Michael W. Mahoney; Talita Perciano; Gunther H. Weber; Ross Maciejewski (IEEE Computer Graphics and Applications, 2025)