About

I’m a cognitive neuroscientist interested in understanding what are the crucial bits of the brain machinery that underpin the human capacity to understand spoken language. I’m currently achieving this by modeling brain activity recorded during audiobook listening. Checkout the projects tab for more info on my work.

Interests

  • cognitive neuroscience, electrophysiology
  • natural language processing
  • artificial neural networks
  • data visualization, open science

Education

  • Postdoctoral Fellow, 2020--present

    Johns Hopkins University, Department of Psychological and Brain Sciences

  • PhD candidate in Cognitive Neuroscience, 2016--2020

    Donders Institute for Brain, Cognition and Behaviour

  • MSc in Cognitive Neuroscience, 2016

    Radboud University, Donders Institute for Brain, Cognition and Behaviour

Projects

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All research other

Neuronal memory for processing sequences with non-adjacent dependencies

Probing the memory capacity of spiking neural networks on a working memory task
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End-to-end encoding models of MEG dynamics during narrative comprehension

Modeling neuronal timescales for language with recurrent neural networks and MEG.

Predictive language comprehension and neural synchrony

Magnetoencephalography meets natural language processing
PDF Code

Open Science Community Nijmegen

A network of scholars to accelerate the adoption of open science practices in Nijmegen
Code Follow www

Foundations of Cognition Series

Discussing the foundational puzzles in the sciences of mind and brain
www

Recent publications

Quickly discover relevant content by filtering publications.

Frequency-specific brain dynamics related to prediction during language comprehension

Do brain rhythms and neural synchrony relate to how predictable the words you hear are?
PDF Code Project DOI

Probabilistic language models in cognitive neuroscience: Promises and pitfalls

A review and a reflection on why we’d want to use NLP techniques in cognitive neuroscience of language.
PDF DOI

Eye tracking measures as indicators of readability for machine-translated texts

Investigating whether your eyes can tell us how well or how poorly google translate did its job.
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Tooling

overview of current tooling stack I use for my work

python, pyTorch, Jupyter Notebook

data wrangling, data viz, stats

R, Rmarkdown

data wrangling, data viz, scientific writing

MATLAB

MEG/EEG data analysis

Git

version control

GitHub

version control, collaborative projects

markdown

collaborative writing

Zotero

bibliography management

Popular Topics

Academic cognitive neuroscience deep learning Demo eye-tracking language modeling language models machine translation MEG neural networks ongoing open science other philosophy of science plot R Markdown regression research spiking neural networks suprisal

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