Riccardo Cusinato

About

I am a physicist and computer scientist passionate about Neuroscience, Data Science, and Statistics. I am interested in neuroscience applications in the pharmaceutical industry (where I did two internships at Roche and J&J) and in the clinical context in general.

Work experience

• Statistics Intern Jul 2023 - Oct 2023
  Johnson&Johnson, Basel, Switzerland
  Within the Manufacturing and Applied Statistics (MAS) group in the Statistics and Decision Sciences (SDS) department, I development a machine learning (ML) algorithm for the analysis of chromatography data. I also developed an R Shiny application for making the adoption of the model easier and wider.


• Data Science Intern (Master's Thesis) Mar 2020 - Aug 2021
  Roche, Basel, Switzerland
  In the Electrophysiology group in the Neuroscience Research department, I analyzed time series data from accelerometer and Electroencephalogram (EEG) in mice with supervised and unsupervised Machine Learning algorithms.
  The work resulted in a publication describing an unsupervised sleep staging algorithm robust to different recording settings and disease models:
  Cusinato, R., Gross, S., et al. (2024) Workflow for the unsupervised clustering of sleep stages identifies light and deep sleep in electrophysiological recordings in mice. Journal of Neuroscience Methods.

Academic experience

• PhD Computer Science Sep 2021 - Sep 2025
  University of Bern, Bern, Switzerland
• Master's in Physics Oct 2018 - Apr 2021
  University of Padova, Padova, Italy
• Bachelors's in Physics Oct 2015 - Sep 2018
  University of Padova, Padova, Italy

Research

©Neuron volume 107

In my PhD I use Data Science and Machine Learning techniques to make sense of complex brain data. Usually, this data takes the form of multivariate electrophysiological signals, for which computational models are needed.

Publications

1. Cusinato, R., et al. (2024), Sleep modulates neural timescales and spatiotemporal integration in the human cortex. Sleep modulates neural timescales and spatiotemporal integration in the human cortex. Biorxiv.


2. Cusinato, R., Gross, S., et al. (2024) Workflow for the unsupervised clustering of sleep stages identifies light and deep sleep in electrophysiological recordings in mice. Journal of Neuroscience Methods.


3. Cusinato, R., Alnes, S. L., et al. (2023) Intrinsic neural timescales in the temporal lobe support an auditory processing hierarchy. Journal of Neuroscience.

Contact

I'd you'd like to discuss anything or ask me a question, please contact me here:

email: r......@unibe.ch

Elements

i = 0;

while (!deck.isInOrder()) {
    print 'Iteration ' + i;
    deck.shuffle();
    i++;
}

print 'It took ' + i + ' iterations to sort the deck.';