Lavinia Moretti is a Ph.D. candidate and doctoral researcher at ETH Zurich since March 2025. She holds a Bachelor’s degree from Politecnico di Milano and a Master’s degree from ETH Zurich in Biomedical Engineering, specializing in electronics and data science.
Her research is centered on advancing digital biomarker discovery and health informatics by developing innovative software tools for data collection in clinical trials. She applies machine learning and statistical techniques to analyze complex health data, with a particular focus on asthma disease.
Lavinia’s expertise combines biomedical engineering, software development, and data science, with a focus on bio-signal sensing, processing, and analysis for wearable medical devices. Her professional experience includes work in digital biomarkers, clinical data analysis, and wearable technology, having contributed to impactful projects at companies such as IDUN Technologies and Roche.
For her Master’s thesis, she created a custom database and sensor fusion algorithm using signal processing and deep learning to predict bladder volume states in Spinal Cord Injury patients, also developing the wearable device used during data collection integrating hardware design, firmware development, software pipeline for storage and analytics.