| 2024 | CHI | The Situate AI Guidebook: Co-Designing a Toolkit to Support Multi-Stakeholder, Early-stage Deliberations Around Public Sector AI Proposals. | Anna Kawakami, Amanda Coston, Haiyi Zhu, Hoda Heidari, Kenneth Holstein |
| 2024 | ICML | Predictive Performance Comparison of Decision Policies Under Confounding. | Luke Guerdan, Amanda Coston, Ken Holstein, Steven Wu |
| 2021 | ICML | Characterizing Fairness Over the Set of Good Models Under Selective Labels. | Amanda Coston, Ashesh Rambachan, Alexandra Chouldechova |
| 2020 | AIME | Neural Topic Models with Survival Supervision: Jointly Predicting Time-to-Event Outcomes and Learning How Clinical Features Relate. | Linhong Li, Ren Zuo, Amanda Coston, Jeremy C. Weiss, George H. Chen |
| 2020 | ICLR | Conditional Learning of Fair Representations. | Han Zhao, Amanda Coston, Tameem Adel, Geoffrey J. Gordon |
| 2019 | AIES | Risk Assessments and Fairness Under Missingness and Confounding. | Amanda Coston |
| 2019 | AIES | Fair Transfer Learning with Missing Protected Attributes. | Amanda Coston, Karthikeyan Natesan Ramamurthy, Dennis Wei, Kush R. Varshney, Skyler Speakman, Zairah Mustahsan, Supriyo Chakraborty |