Bianca Trovò

• Teaching and mentoring in Data Science & Data Analysis • Supporting learners in Python, ML, DL, statistics and applied analytics • Contributing AI expertise and curriculum improvements

• Quantitative research and scientific data analysis • Support for datasets in biology, neuroscience, and machine learning • Data cleaning, modeling, and reporting

• Prepared daily teaching sessions by reviewing lectures, slides, videos, and coding notebooks for machine learning, deep learning, modeling, and computational neuroscience modules. • Lectured c ore M L / D L topics (GLMs, dimensionality reduction, optimization, regularization, NLP, generative models, RL) and coached two cohorts (~15 MSc/PhD students each) through Python/PyTorch live coding exercises. • Guided 3-week group research projects, helping teams design models, analyze data, and prepare published abstracts and final presentations. • Reported student progress and blockers to program staff and faculty mentors to ensure a smooth, supportive learning experience.

• Executed machine learning projects in Python for National AI Certification. Built ETL pipelines, developed predictive models, and implemented neural networks for crime visualization, Spotify predictions, and image/audio denoising. • Coordinated a team of 4 for the demo day project, developing CNN/RNN models (TensorFlow, PyTorch) to decode EEG signals.

• Designed and executed large-scale M/EEG experiments (movement- related signals), producing four datasets with over 60 participants. • Built end-to-end data pipelines for cleaning, preprocessing, feature extraction, and statistical modeling (MATLAB). • Managed cross-team coordination (clinicians, engineers, researchers), and regulatory documentation, budgeted experiments up to 100k.