Guillem Bonafos

My research is driven by a fundamental question: how does language emerge?

I investigate this question by studying children’s vocalizations during the pre-linguistic stage, viewing them as a window into the mechanisms that precede and shape language acquisition. In particular, I examine the information structure of early vocal behavior and the extent to which these signals can predict subsequent developmental trajectories.

Methodologically, my work combines machine learning and topological data analysis to uncover the structure of high-dimensional vocalization data. I aim to learn representations that are both maximally informative and intrinsically interpretable, allowing links to be drawn between computational structure and developmental processes. At the same time, the developmental dynamics of vocalizations provide a principled framework for probing, constraining, and ultimately disentangling these learned representational spaces.