Topic: Probabilistic AI/ML algorithms leveraging Virtual Brain Twins.

Project: State-of-the-art Bayesian inference on virtual brain models for brain diseases; Deep neural density estimators for flexible simulation-based inference; Adaptive Monte Carlo for automatic statistical estimation.

Supervisor: Prof. Viktor Jirsa

Thesis: Analytical and numerical studies of thalamo-cortical neural population models during general anesthesia.

My thesis investigated the mechanisms underlying specific EEG pattern changes during propofol-induced anesthesia, linking anesthetic effects at the microscopic single neuron level to macroscopic-scale observables.

Supervisor: Dr. Axel Hutt

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Thesis: Effect of the duration of synaptic activity on a neuronal loop with delayed feedback.

Supervisor: Dr. Alireza Valizadeh

⬇ View Thesis (Persian)