Her research interests include the design and analysis of algorithms, computational geometry, data mining and machine learning, and the application of such algorithms to interdisciplinary data. Sorelle is one of the organizers of the Workshop on Fairness, Accountability, and Transparency in Machine Learning and has received a Data & Society Fellowship and recent 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 holds a Ph.D. in Computer Science from the University of Maryland, College Park.