Melody Dye

BIDS Data Science Fellow, Moore/Sloan
Postdoctoral Scholar, School of Information

Real name: 
Melody Dye

Melody is a postdoctoral fellow and lecturer in Natural Language Processing and Deep Learning with the School of Information. Her research explores the cognitive and social mechanisms underlying language variation and change, using computational modeling approaches from learning and information theory, large-scale text mining, and behavioral experimentation. She earned her PhD in Cognitive Science and Computational Linguistics from Indiana University, Bloomington, where she was supported by an NSF Graduate Research Fellowship.