Academic Background: Biophotonics, Laval University; MSc, Artificial Intelligence, Isfahan University of Technology.
Email: poormosavi.m@gmail.com
Research Contribution: Contributing to statistical and machine-learning analyses, including a recent project on perceptual auditory disorders focused on predictive modelling of bothersome tinnitus and hypersensitivity to sounds using multimodal clinical datasets. Responsibilities include data preprocessing, feature selection, model development and evaluation, interpretability analyses, and support for scientific writing.
Background: Marziyeh’s research background spans computational neuroscience, multimodal biosignal analysis, and applied machine learning for biomedical data. She developed EMANPI, an open-source Python toolbox for multimodal Ca²⁺ imaging analysis (DOI: 10.5281/zenodo.15658292) and has published research involving machine-learning approaches to data prediction.
