Amanda Coston

Assistant Professor, AI2050 Early Career Fellow

Year

2023
Program

AI2050
Institution

University of California, Berkeley
Field of Study

Machine Learning and Statistics
Location

USA

Amanda Coston is an Assistant Professor of Statistics at UC Berkeley. Her research addresses real-world data problems that challenge the validity, reliability, and equity of algorithmic decision support systems and data-driven policy-making. Amanda earned her PhD in Machine Learning and Public Policy at Carnegie Mellon University where she was advised by Alexandra Chouldechova and Edward H. Kennedy. After her PhD, Amanda worked at Microsoft Research on the Machine Learning and Statistics Team as a postdoc researcher. Amanda is a Rising Star in EECS, Machine Learning, and Data Science, a Meta Research PhD Fellow, NSF GRFP Fellow, K & L Gates Presidential Fellow in Ethics and Computational Technologies, and Tata Consultancy Services Presidential Fellow. Her work has been recognized by best paper awards and featured in The Wall Street Journal and VentureBeat.