My main research interests lie in speech and language
processing at different timescales. Specifically, I am
interested in how the brain encodes and decodes linguistic
information through time by building features spaces with
the use of explicit linguistic theories in combination with
Large Language models.
Currently, I am part of the ARENA (Abstract Representation
in Neural Architectures) research unit which focuses on how
different levels of knowledge abstraction, for example
syntactic and semantic information, are encoded by the
brain both temporally and spatially. To do so, I employ
machine learning approaches to behavioral data and neural
data, recorded with Electroencephalography (EEG) and
Magnetoencephalography (MEG).