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Grace Smith-Vidaurre, PhD

Research Statement

Vocal learning, or the ability to learn vocalizations from social companions, is a fundamental component of human language. This rare trait has also evolved in several phylogenetically distant mammalian and avian taxa. While there has been a lot of interest in how this cognitive trait evolved, there is still much to discover about how vocal communication systems shaped by social learning can change once they are in place.

My research focuses on how vocal communication systems that rely on social learning may be flexible or constrained over short evolutionary timescales. Research in my lab addresses two overarching functional and mechanistic questions. First, why are flexible vocal communication systems important? Second, how might early social experiences constrain flexible vocal communication?

My lab uses a data science perspective to address questions spanning ecology, evolution, and neuroscience. We develop computational pipelines to process and analyze biological data across different scales of biological organization, as well as new tools to collect behavioral data. Our main study systems for this research are parrots (monk parakeets) and songbirds (zebra finches). I am open to discussing research projects with other study systems, including mathematical modeling approaches.