Featured Projects

Deploying a pretrained language model (BART-MNLI) to classify the experience of a cohort of subjects undergoing a breathwork intervention.

Used a data-driven approach (GLM-HMM) to predict an animal's performance in a naturalistic setup by only having access to facial expression.

Solving a simple classification task with a bio-inspired Neural Network.

Developed a general and simple computational method that allows neuroscientists to check the relevance of trial-averages (such as firing rates, PSTHs) in their datasets. Validated this method in two different datasets.

Using optimized CNNs to classify music genres, using Bayesian Optimization and Transfer Learning.

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