FacIt: Factorizing Tensors into Interpretable and Scrutinizable Patterns. - Xidao Wen; Konstantinos Pelechrinis; Yu-Ru Lin; Xi Liu 011; Yongsu Ahn; Nan Cao 001 (IEEE VIS (Short Papers), 2019)

PolicyFlow: Interpreting Policy Diffusion in Context. - Yongsu Ahn; Yu-Ru Lin (ACM Trans. Interact. Intell. Syst., 2020)

FairSight: Visual Analytics for Fairness in Decision Making. - Yongsu Ahn; Yu-Ru Lin (IEEE Trans. Vis. Comput. Graph., 2020)

Improving Citizen-initiated Police Reform Efforts through Interactive Design: A Case Study in Allegheny County. - Yongsu Ahn; Eliana Beigel; Noah Braun; Collin Griffin; Sera Linardi; Blair Mickles; Emmaline Rial (EAAMO, 2022)

Tribe or Not? Critical Inspection of Group Differences Using TribalGram. - Yongsu Ahn; Muheng Yan; Yu-Ru Lin; Wen-Ting Chung; Rebecca Hwa (ACM Trans. Interact. Intell. Syst., 2022)

HungerGist: An Interpretable Predictive Model for Food Insecurity. - Yongsu Ahn; Muheng Yan; Yu-Ru Lin; Zian Wang (IEEE Big Data, 2023)

ESCAPE: Countering Systematic Errors from Machine's Blind Spots via Interactive Visual Analysis. - Yongsu Ahn; Yu-Ru Lin; Panpan Xu; Zeng Dai (CHI, 2023)

VISPUR: Visual Aids for Identifying and Interpreting Spurious Associations in Data-Driven Decisions. - Xian Teng; Yongsu Ahn; Yu-Ru Lin (CoRR, 2023)

Exploring Teachers' Perception of Artificial Intelligence: The Socio-emotional Deficiency as Opportunities and Challenges in Human-AI Complementarity in K-12 Education. - Soon-young Oh; Yongsu Ahn (AIED (2), 2024)

Interactive Counterfactual Exploration of Algorithmic Harms in Recommender Systems. - Yongsu Ahn; Quinn K. Wolter; Jonilyn Dick; Janet Dick; Yu-Ru Lin (VDS@VIS, 2024)

Gender Bias in LLM-generated Interview Responses. - Haein Kong; Yongsu Ahn; Sangyub Lee 006; Yunho Maeng (CoRR, 2024)

V: Visual Aids for Identifying and Interpreting Spurious Associations in Data-Driven Decisions. - Xian Teng; Yongsu Ahn; Yu-Ru Lin (IEEE Trans. Vis. Comput. Graph., 2024)

Break Out of a Pigeonhole: A Unified Framework for Examining Miscalibration, Bias, and Stereotype in Recommender Systems. - Yongsu Ahn; Yu-Ru Lin (ACM Trans. Intell. Syst. Technol., 2024)

Human-centered explanation does not fit all: The interplay of sociotechnical, cognitive, and individual factors in the effect AI explanations in algorithmic decision-making. - Yongsu Ahn; Yu-Run Lin; Malihe Alikhani; Eunjeong Cheon (CoRR, 2025)