During my PhD, I investigate how infants learn patterns and regularities in their environment through statistical learning. My research explores how caregiver predictability shapes infant learning and how these early learning processes relate to later developmental outcomes, such as language skills.
To address these questions, I use OPM MEG, a novel neuroimaging technique that allows us to measure infant brain activity with high spatial and temporal resolution.
Prior to joining the BabyBRAIN group, I studied psychology, neuroscience, and data science. I am passionate about applying data science methods to questions in neuroscience, particularly to understanding how the infant brain develops and learns.
