Sotabase

Career

· Assistant Professor, UC Berkeley Department of Statistics2024–

Publications (27)

Counterfactual risk assessments, evaluation, and fairness
FAT* · 2019
128
cited
Conditional Learning of Fair Representations
International Conference on Learning Representations · 2019
124
cited
Fair Transfer Learning with Missing Protected Attributes
AAAI/ACM Conference on AI, Ethics, and Society · 2019
115
cited
Characterizing Fairness Over the Set of Good Models Under Selective Labels
International Conference on Machine Learning · 2021
92
cited
Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy
Conference on Fairness, Accountability and Transparency · 2020
77
cited
A Validity Perspective on Evaluating the Justified Use of Data-driven Decision-making Algorithms
2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML) · 2022
47
cited
The Situate AI Guidebook: Co-Designing a Toolkit to Support Multi-Stakeholder, Early-stage Deliberations Around Public Sector AI Proposals
International Conference on Human Factors in Computing Systems · 2024
39
cited
Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making
Conference on Fairness, Accountability and Transparency · 2023
37
cited
Counterfactual Predictions under Runtime Confounding
Neural Information Processing Systems · 2020
35
cited
Counterfactual Prediction Under Outcome Measurement Error
Conference on Fairness, Accountability and Transparency · 2023
18
cited
Distributionally Robust Survival Analysis: A Novel Fairness Loss Without Demographics
ML4H@NeurIPS · 2022
18
cited
Examining risks of racial biases in NLP tools for child protective services
Conference on Fairness, Accountability and Transparency · 2023
17
cited
Studying Up Public Sector AI: How Networks of Power Relations Shape Agency Decisions Around AI Design and Use
Proc. ACM Hum. Comput. Interact. · 2024
15
cited
Counterfactual Risk Assessments under Unmeasured Confounding
arXiv.org · 2022
14
cited
Neural topic models with survival supervision: Jointly predicting time-to-event outcomes and learning how clinical features relate
Conference on Artificial Intelligence in Medicine in Europe · 2020
6
cited
Robust Design and Evaluation of Predictive Algorithms under Unobserved Confounding
2022
6
cited
Bridging Prediction and Intervention Problems in Social Systems
arXiv.org · 2025
4
cited
The role of the geometric mean in case-control studies
2022
2
cited
Proceedings of NeurIPS 2018 Workshop on Machine Learning for the Developing World: Achieving Sustainable Impact
arXiv.org · 2018
1
cited
Recentering Validity Considerations through Early-Stage Deliberations Around AI and Policy Design
arXiv.org · 2023
1
cited
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Amanda Coston | Researcher Profile | Sotabase | Sotabase