As a Research Fellow, Alexandra Chouldechova’s research focuses on questions of algorithmic fairness and accountability in data-driven decision making systems in domains including criminal justice and human services. She studies how statistical methodologies can aid in developing human-centered data-driven decision making systems that mitigate biases and reduce disparities. At the Partnership on AI, Alexandra’s work centers on measuring and mitigating algorithmic bias in recidivism datasets.

She received her B.Sc. from the University of Toronto in 2009, and in 2014 she completed her Ph.D. in Statistics at Stanford University. While at Stanford, she also worked at Google and Symantec on developing statistical assessment methods for information retrieval systems.

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