RAWLSNET: Altering Bayesian Networks to Encode Rawlsian Fair Equality of Opportunity. - David Liu 006; Zohair Shafi; William Fleisher; Tina Eliassi-Rad; Scott Alfeld (AIES, 2021)

Examining Responsibility and Deliberation in AI Impact Statements and Ethics Reviews. - David Liu 006; Priyanka Nanayakkara; Sarah Ariyan Sakha; Grace Abuhamad; Su Lin Blodgett; Nicholas Diakopoulos; Jessica R. Hullman; Tina Eliassi-Rad (AIES, 2022)

Identifying and Mitigating Instability in Embeddings of the Degenerate Core. - David Liu 006; Tina Eliassi-Rad (CoRR, 2022)

BiaScope: Visual Unfairness Diagnosis for Graph Embeddings. - Agapi Rissaki; Bruno Scarone; David Liu 006; Aditeya Pandey; Brennan Klein; Tina Eliassi-Rad; Michelle A. Borkin (CoRR, 2022)

Group fairness without demographics using social networks. - David Liu 006; Virginie Do; Nicolas Usunier; Maximilian Nickel (FAccT, 2023)

STABLE: Identifying and Mitigating Instability in Embeddings of the Degenerate Core. - David Liu 006; Tina Eliassi-Rad (SDM, 2023)

Re-visiting Skip-Gram Negative Sampling: Dimension Regularization for More Efficient Dissimilarity Preservation in Graph Embeddings. - David Liu 006; Arjun Seshadri; Tina Eliassi-Rad; Johan Ugander (CoRR, 2024)

When Collaborative Filtering is not Collaborative: Unfairness of PCA for Recommendations. - David Liu 006; Jackie Baek; Tina Eliassi-Rad (FAccT, 2025)

Forecasting Faculty Placement from Patterns in Co-authorship Networks. - Samantha Dies; David Liu 006; Tina Eliassi-Rad (CoRR, 2025)