Sorelle Friedler is an Associate Professor of Computer Science at Haverford College and the Assistant Director for Data and Democracy in the White House Office of Science and Technology Policy. Her research focuses on the fairness and interpretability of machine learning algorithms, with applications from criminal justice to materials discovery.

Sorelle is a Co-Founder and former Executive Committee Member of the ACM Conference on Fairness, Accountability, and Transparency (FAT*) as well as a former Program Committee Co-Chair of FAT* and FAT/ML. She has received a Mozilla grant, Fellowship, and NSF grant for her work on preventing discrimination in machine learning. Her work on this topic has been featured in IEEE Spectrum, Gizmodo, and NBC News and she has been interviewed about algorithmic fairness by the Guardian, Bloomberg, and NPR.

Sorelle is the recipient, along with chemistry professors Josh Schrier and Alex Norquist, of a DARPA contract and two NSF Grants to apply data mining techniques to materials chemistry data to speed up materials discovery, using interpretable machine learning techniques to inform scientific hypotheses. One paper on this work was featured on the cover of Nature and was covered by The Wall Street Journal and Scientific American.

Before Haverford, Sorelle was a software engineer at Alphabet (formerly Google), where she worked in the X lab and in search infrastructure. She holds a Ph.D. in Computer Science from the University of Maryland, College Park, and a B.A. from Swarthmore College.