Amanda Coston
UC Berkeley
Amanda Coston is an Assistant Professor in the Department of Statistics at UC Berkeley. Her work considers how -- and when -- machine learning and causal inference can improve decision-making in societally high-stakes settings.
Her research addresses real-world data problems that challenge the validity, equity, and reliability of algorithmic decision support systems and data-driven policy-making. A central focus of her research is identifying when algorithms, data used for policy-making, and human decisions disproportionately impact marginalized groups.