Nicola Ricci MacCarini
Research Assistant Internship @Università Degli Studi Di Ferrara
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WORK HISTORY
Research Assistant Internship @Università Degli Studi Di Ferrara
Ferrara, IT
Working on my curricular internship, where I focus on validating and improving Machine Learning algorithms for the automatic recognition of EEG spindles. The goal is to support the diagnosis of EE-SWAS in children with sleep-facilitated focal epilepsy and neuropsychological comorbidities.My work includes- Testing ML algorithms on data from 100+ patients and comparing results with current gold standards- Enhancing models to analyze not only spindle rate in N2 but also qualitative features such as duration, symmetry, and interhemispheric delay- Designing improvements to push these algorithms toward becoming the new state of the art in EEG spindle recognition and description- Contributing to scientific publications on ML applications in healthcare
EDUCATION
Università degli Studi di Ferrara
Laurea triennale
ABOUT NICOLA RICCI MACCARINI
I’m a 21-year-old Computer Science student at the University of Ferrara specializing in the intersection of Artificial Intelligence, Machine Learning, and Neuroscience. My work focuses on applying data-driven and computational approaches to understand and model brain activity, with a particular interest in EEG signal analysis and AI-assisted diagnostics.Through my academic path and hands-on research experience, I’ve developed strong skills in Python, deep learning frameworks, and end-to-end ML pipelines. I’m especially interested in exploring how intelligent systems can enhance clinical decision-making and advance our understanding of neural processes.Beyond neuroscience, I enjoy building AI-powered applications that address real-world problems from data preprocessing and model optimization to deploying scalable, user-focused solutions. I’m constantly experimenting with modern AI tools such as Hugging Face and Ollama to push my models toward greater efficiency and interpretability.My goal is to contribute to the development of smarter, more accessible AI solutions that bridge the gap between computational intelligence and human health.
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